| Title: | A Collection of Univariate Data Sets |
|---|---|
| Description: | A collection of widely used univariate data sets of various applied domains on applications of distribution theory. The functions allow researchers and practitioners to quickly, easily, and efficiently access and use these data sets. The data are related to different applied domains and as follows: Bio-medical, survival analysis, medicine, reliability analysis, hydrology, actuarial science, operational research, meteorology, extreme values, quality control, engineering, finance, sports and economics. The total 100 data sets are documented along with associated references for further details and uses. |
| Authors: | Muhammad Imran [aut, cre], M.H Tahir [ctb], Farrukh Jamal [ctb] |
| Maintainer: | Muhammad Imran <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 0.1 |
| Built: | 2025-03-01 04:05:10 UTC |
| Source: | https://github.com/cran/DataSetsUni |
The function allows to provide the 30 observations of the March precip- itation (in inches) in Minneapolis/St Paul.
data_MPrecipitationdata_MPrecipitation
data_MPrecipitation |
A vector of (non-negative integer) values. |
Data consists of 30 observations of the March precip- itation (in inches) in Minneapolis/St Paul. Recently, it is used by Usman and Haq (2020) and fitted the Marshall-Olkin extended inverted Kumaraswamy distribution.
data_MPrecipitation gives the March precip- itation (in inches) in Minneapolis/St Paul.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Usman, R. M., & ul Haq, M. A. (2020). The Marshall-Olkin extended inverted Kumaraswamy distribution: Theory and applications. Journal of King Saud University-Science, 32(1), 356-365.
Hinkley, D. (1977). On quick choice of power transformation. Journal of the Royal Statistical Society: Series C (Applied Statistics), 26(1), 67-69.
x<-data_MPrecipitation summary(x)x<-data_MPrecipitation summary(x)
A collection of widely used univariate data sets of various applied domains on applications of distribution theory. The functions allow researchers and practitioners to quickly, easily, and efficiently access and use these data sets. The data are related to different applied domains and as follows: Bio-medical, survival analysis, medicine, reliability analysis, hydrology, actuarial science, operational research, meteorology, extreme values, quality control, engineering, finance, sports and economics. The total 100 data sets are documented along with associated references for further details and uses.
| Package: | DataSetsUni |
| Type: | Package |
| Version: | 0.1 |
| Date: | 2023-05-10 |
| License: | GPL-2 |
Muhammad Imran <[email protected]>
Muhammad Imran <[email protected]>, M.H Tahir <[email protected]> and Farrukh Jamal <[email protected]>.
The function allows to provide the monthly actual taxes revenue in Egypt from January 2006 to November 2010.
data_Taxesdata_Taxes
data_Taxes |
A vector of (non-negative integer) values. |
The data set consists of the monthly actual taxes revenue in Egypt from January 2006 to November 2010. Recently, it is used by Ali et al. (2022) and fitted the odd Burr-III Lomax distribution.
data_Taxes gives the monthly actual taxes revenue in Egypt.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Ali, M., Khalil, A., Mashwani, W. K., Alrajhi, S., Al-Marzouki, S., & Shah, K. (2022). A novel fréchet-type probability distribution: its properties and applications. Mathematical Problems in Engineering, 2022, 1-14.
Jamal, F., Nasir, M. A., Tahir, M. H., & Montazeri, N. H. (2017). The odd Burr-III family of distributions. Journal of Statistics Applications and Probability, 6(1), 105-122.
Owoloko, E. A., Oguntunde, P. E., & Adejumo, A. O. (2015). Performance rating of the transmuted exponential distribution: an analytical approach. SpringerPlus, 4, 1-15.
Nassar, M. M., & Nada, N. K. (2011). The beta generalized Pareto distribution. Journal of Statistics: Advances in Theory and Applications, 6(1/2), 1-17.
x<-data_Taxes summary(x)x<-data_Taxes summary(x)
The function allows to provide the distributional behavior of the mortality of retired people on disability of the Mexican Institute of Social Security.
data_actuarialmdata_actuarialm
data_actuarialm |
A vector of (non-negative integer) values. |
The data describes the distributional behavior of the mortality of retired people on disability of the Mexican Institute of Social Security. Recently, it is used by Tahir et al. (2021) and fitted the Kumaraswamy Pareto IV distribution.
data_actuarialm gives the mortality of retired people.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Tahir, M. H., Cordeiro, G. M., Mansoor, M., Zubair, M., & Alzaatreh, A. (2021). The Kumaraswamy Pareto IV Distribution. Austrian Journal of Statistics, 50(5), 1-22.
Balakrishnan, N., Leiva, V., Sanhueza, A., & Cabrera, E. (2009). Mixture inverse Gaussian distributions and its transformations, moments and applications. Statistics, 43(1), 91-104.
x<-data_actuarialm summary(x)x<-data_actuarialm summary(x)
The function allows to provide the survival times (in days) of 73 patients who diagnosed with acute bone cancer.
data_acutebcancerdata_acutebcancer
data_acutebcancer |
A vector of (non-negative integer) values. |
The data represents the survival times (in days) of 73 patients who diagnosed with acute bone cancer. Recently, the data set is used by Klakattawi, H. S. (2022) and fitted a new extended Weibull distribution.
data_acutebcancer gives the survival times (in days) of 73 patients who diagnosed with acute bone cancer.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Klakattawi, H. S. (2022). Survival analysis of cancer patients using a new extended Weibull distribution. Plos one, 17(2), e0264229.
Alanzi, A. R., Imran, M., Tahir, M. H., Chesneau, C., Jamal, F., Shakoor, S., & Sami, W. (2023). Simulation analysis, properties and applications on a new Burr XII model based on the Bell-X functionalities.
Mansour, M., Yousof, H. M., Shehata, W. A., & Ibrahim, M. (2020). A new two parameter Burr XII distribution: properties, copula, different estimation methods and modeling acute bone cancer data. Journal of Nonlinear Science and Applications, 13(5), 223-238.
data_Bcancer, data_bloodcancer
x<-data_acutebcancer summary(x)x<-data_acutebcancer summary(x)
The function allows to provide the survival times in weeks, of 33 patients suffering from acute myelogenous leukemia.
data_Myelogenousdata_Myelogenous
data_Myelogenous |
A vector of (non-negative integer) values. |
The data represents the survival times in weeks, of 33 patients suffering from acute myelogenous leukemia. Recently, it is used by Jamal et al. (2017) and fitted the odd Burr-III Lomax distribution.
data_Myelogenous gives the survival times in weeks, of 33 patients suffering from acute myelogenous leukemia.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Jamal, F., Nasir, M. A., Tahir, M. H., & Montazeri, N. H. (2017). The odd Burr-III family of distributions. Journal of Statistics Applications and Probability, 6(1), 105-122.
Feigl, P., & Zelen, M. (1965). Estimation of exponential survival probabilities with concomitant information. Biometrics, 826-838.
data_acutebcancer, data_leukemia, data_bloodcancer, data_airborne
x<-data_Myelogenous summary(x)x<-data_Myelogenous summary(x)
The function allows to provide the failure times of the air conditioning system of an airplane (in hours).
data_acfailuredata_acfailure
data_acfailure |
A vector of (non-negative integer) values. |
The data set consists of the failure times of the air conditioning system of an airplane (in hours). Recently, it is used by Bantan et al. (2020) and fitted the unit-Rayleigh distribution.
data_acfailure gives the failure times of the air conditioning system of an airplane (in hours).
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bantan, R. A., Chesneau, C., Jamal, F., Elgarhy, M., Tahir, M. H., Ali, A., ... & Anam, S. (2020). Some new facts about the unit-Rayleigh distribution with applications. Mathematics, 8(11), 1954.
Linhart, H., & Zucchini, W. (1986). Model selection. John Wiley & Sons.
data_failureairc, data_electronicf
x<-data_acfailure summary(x)x<-data_acfailure summary(x)
The function allows to provide the unit interval failure times of the air conditioning system of an airplane (in hours).
data_acfailureunitdata_acfailureunit
data_acfailureunit |
A vector of (non-negative integer) values. |
The unit interval data set consists of the failure times of the air conditioning system of an airplane (in hours). Recently, it is used by Bantan et al. (2020) and fitted the unit-Rayleigh distribution.
data_acfailureunit gives the failure times of the air conditioning system of an airplane (in hours).
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bantan, R. A., Chesneau, C., Jamal, F., Elgarhy, M., Tahir, M. H., Ali, A., ... & Anam, S. (2020). Some new facts about the unit-Rayleigh distribution with applications. Mathematics, 8(11), 1954.
Linhart, H., & Zucchini, W. (1986). Model selection. John Wiley & Sons.
x<-data_acfailureunit summary(x)x<-data_acfailureunit summary(x)
The function allows to provide the daily ozone measurements in New York, May–September 1973.
data_airpollutiondata_airpollution
data_airpollution |
A vector of (non-negative integer) values. |
The data represents the daily ozone measurements in New York, May–September 1973. Recently, it is used by Nadarajah (2008) and fitted a truncated inverted beta distribution.
data_airpollution gives the daily ozone measurements.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Nadarajah, S. (2008). A truncated inverted beta distribution with application to air pollution data. Stochastic Environmental Research and Risk Assessment, 22, 285-289.
x<-data_airpollution summary(x)x<-data_airpollution summary(x)
The function allows to provide the effects of variations in airborne exposure on the concentration of urinary metabolites.
data_airbornedata_airborne
data_airborne |
A vector of (non-negative integer) values. |
The data relates to the effects of variations in airborne exposure on the concentration of urinary metabolites. Recently, it is used by Peter et al. (2021) and fitted the Gamma odd Burr III-G family of distributions.
data_airborne gives the effects of variations in airborne exposure on the concentration of urinary metabolites.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Peter, P. O., Oluyede, B., Bindele, H. F., Ndwapi, N., & Mabikwa, O. (2021). The Gamma Odd Burr III-G Family of Distributions: Model, Properties and Applications. Revista Colombiana de Estadística, 44(2), 331-368.
Kumagai, S., & Matsunaga, I. (1995). Physiologically based pharmacokinetic model for acetone. Occupational and environmental medicine, 52(5), 344-352.
data_analgesic, data_dpatients
x<-data_airborne summary(x)x<-data_airborne summary(x)
The function allows to provide the 30 patients were assessed at baseline, post treatment, and a 6-month follow-up using the Wolf Mo- tor Function Test as primary outcome measure. The test con- sists of 17 tasks with two strength and 15 timed tasks which vary from gross shoulder movements to complex finger grips. The measurement was done by the analysis of videotapes.
data_videotapesdata_videotapes
data_videotapes |
A vector of (non-negative integer) values. |
The 30 patients were assessed at baseline, post treatment, and a 6-month follow-up using the Wolf Mo- tor Function Test as primary outcome measure. The test con- sists of 17 tasks with two strength and 15 timed tasks which vary from gross shoulder movements to complex finger grips. The measurement was done by the analysis of videotapes. Recently, it is used by Nassar and Elmasry (2012) and fitted the generalized logistic distribution.
data_videotapes gives the measurements by the analysis of video tapes.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Nassar, M. M., & Elmasry, A. (2012). A study of generalized logistic distributions. Journal of the Egyptian Mathematical Society, 20(2), 126-133.
x<-data_videotapes summary(x)x<-data_videotapes summary(x)
The function allows to provide the 52 ordered annual maximum antecedent rainfall measurements in mm from Maple Ridge in British Columbia, Canada.
data_rainfalldata_rainfall
data_rainfall |
A vector of (non-negative integer) values. |
The data represents the 52 ordered annual maximum antecedent rainfall measurements in mm from Maple Ridge in British Columbia, Canada. Recently, it is used by Nadarajah and Eljabri (2014) and fitted the chen et al.’s extreme value distribution.
data_rainfall gives the annual maximum antecedent rainfall measurements.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Nadarajah, S., & Eljabri, S. (2014). On chen et al.’s extreme value distribution. Journal of Data Science, 12(1), 87-106.
data_MPrecipitation, data_precipitation
x<-data_rainfall summary(x)x<-data_rainfall summary(x)
The function allows to provide annual maximum temperatures at Oxford and Worthing (England), for the period 1901 to 1980.
data_AnnualMaxTdata_AnnualMaxT
data_AnnualMaxT |
A vector of (non-negative integer) values. |
The data describes annual maximum temperatures at Oxford and Worthing (England), for the period 1901 to 1980. Recently, it is used by Tahir et al. (2021) and fitted the Kumaraswamy Pareto IV distribution.
data_AnnualMaxT gives the annual maximum temperatures.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Tahir, M. H., Cordeiro, G. M., Mansoor, M., Zubair, M., & Alzaatreh, A. (2021). The Kumaraswamy Pareto IV Distribution. Austrian Journal of Statistics, 50(5), 1-22.
Weisberg S (2005). Applied Linear Regression. Wiley, New York. ISBN 978-0-471-70409-6.
x<-data_AnnualMaxT summary(x)x<-data_AnnualMaxT summary(x)
The function allows to provide the annual water level behind the high dam during the flood time from 1980 to 2010. The highest water level of the dam is 182 meters (m) above the mean sea level.
data_floodtimedata_floodtime
data_floodtime |
A vector of (non-negative integer) values. |
The data set consists of the annual water level behind the high dam during the flood time from 1980 to 2010. The highest water level of the dam is 182 meters (m) above the mean sea level. Recently, it is used by Khalid and Aslam (2021) and fitted unit Lindley mixture model.
data_floodtime gives the annual water level behind the high dam during the flood time from 1980 to 2010.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Khalid, M., & Aslam, M. (2022). Bayesian Analysis of 3-Component Unit Lindley Mixture Model with Application to Extreme Observations. Mathematical Problems in Engineering, 2022.
Abdel-Latif, M. M., & Yacoub, M. (2011). Effect of change of discharges at Dongola station due to sedimentation on the water losses from Nasser Lake. Nile Basin Water Science & Engineering Journal, 4(1), 86-98.
El-Deen, M. S., Al-Dayian, G. R., & El-Helbawy, A. A. (2014). Statistical inference for Kumaraswamy distribution based on generalized order statistics with applications. British Journal of Mathematics & Computer Science, 4(12), 1710.
data_floodSus, data_flood, data_floodpeak,
x<-data_floodtime summary(x)x<-data_floodtime summary(x)
The function allows to provide the annual yield for the period from 1951 to 2010. The units are tons per hectares.
data_annualylddata_annualyld
data_annualyld |
A vector of (non-negative integer) values. |
The annual yield data set consists of annual yield for the period from 1951 to 2010. The units are tons per hectares. Recently, it is used by Ristić et al. (2015) and fitted the generalized beta exponential distribution.
data_annualyld gives the annual wheat yield.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Ristić, M. M., Popović, B. V., & Nadarajah, S. (2015). Libby and Novick's generalized beta exponential distribution. Journal of Statistical Computation and Simulation, 85(4), 740-761.
x<-data_annualyld summary(x)x<-data_annualyld summary(x)
The function allows to provide the arthritis relief time (in hours). Joint stiffness and pain are the main signs and symptoms of arthritis, and these symptoms usually get worse as people aged.
data_arthritisdata_arthritis
data_arthritis |
A vector of (non-negative integer) values. |
The data consists of 50 individuals with arthritis relief time (in hours). Joint stiffness and pain are the main signs and symptoms of arthritis, and these symptoms usually get worse as people age. Recently, it is used by Alanzi et al. (2023) and fitted a new Burr XII model based on the Bell-X functionalities.
data_arthritis gives the arthritis relief time (in hours).
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alanzi, A. R., Imran, M., Tahir, M. H., Chesneau, C., Jamal, F., Shakoor, S., & Sami, W. (2023). Simulation analysis, properties and applications on a new Burr XII model based on the Bell-X functionalities. Okasha, H. M., & Shrahili, M. (2017). A new extended Burr XII distribution with applications. Journal of Computational and Theoretical Nanoscience, 14(11), 5261-5269.
x<-data_arthritis summary(x)x<-data_arthritis summary(x)
The function allows to provide a test results on the endurance of deep groove ball bearings.
data_blbearingdata_blbearing
data_blbearing |
A vector of (non-negative integer) values. |
The data resulted from a test on the endurance of deep groove ball bearings. Recently, it is used by Badr and Sobahi (2022) and fitted the exponentiated exponential-inverse Weibull model.
data_acfailureunit gives the test results on the endurance of deep groove ball bearings.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Badr, M. M., & Sobahi, G. (2022). The Exponentiated Exponential-Inverse Weibull Model: Theory and Application to COVID-19 Data in Saudi Arabia. Journal of Mathematics, 2022.
Tripathi, H., Dey, S., & Saha, M. (2021). Double and group acceptance sampling plan for truncated life test based on inverse log-logistic distribution. Journal of Applied Statistics, 48(7), 1227-1242.
Lawless, J. F. (2011). Statistical models and methods for lifetime data. John Wiley & Sons.
x<-data_blbearing summary(x)x<-data_blbearing summary(x)
The function allows to provide the Bitcoin exchange rates.
data_Bitcoindata_Bitcoin
data_Bitcoin |
A vector of (non-negative integer) values. |
The data represent the Bitcoin exchange rates. Recently, it is used by Wang et al. (2023) and fitted a new Dagum model.
data_Bitcoin gives the Bitcoin exchange rates.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Wang, Y., Ahmad, Z., Khan, F., Alnagar, D. K., Alsuhabi, H., Alkhairy, I., & Yusuf, M. (2023). Analysis of cryptocurrency exchange rates vs USA dollars using a new Dagum model. Alexandria Engineering Journal, 64, 645-658.
x<-data_Bitcoin summary(x)x<-data_Bitcoin summary(x)
The function allows to provide the remission times (in months) of 128 patients suffering from bladder cancer.
data_bldercancerdata_bldercancer
data_bldercancer |
A vector of (non-negative integer) values. |
The remission times (in months) of 128 patients suffering from bladder cancer. Recently, the data set is used by Bhatti et al. (2019) and fitted the Burr III-Marshal Olkin-Weibull distribution.
data_bldercancer gives the remission times (in months) of 128 patients.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bhatti, F. A., Hamedani, G. G., Korkmaz, M. C., Cordeiro, G. M., Yousof, H. M., & Ahmad, M. (2019). On Burr III Marshal Olkin family: development, properties, characterizations and applications. Journal of Statistical Distributions and Applications, 6, 1-21.
Klakattawi, H. S. (2022). Survival analysis of cancer patients using a new extended Weibull distribution. Plos one, 17(2), e0264229.
Lemonte, A. J., & Cordeiro, G. M. (2013). An extended Lomax distribution. Statistics, 47(4), 800-816.
Lee, E. T., & Wang, J. (2003). Statistical methods for survival data analysis (Vol. 476). John Wiley & Sons.
Muhammad, M., Muhammad, I., & Yaya, A. M. (2018). The Kumaraswamy exponentiated U-quadratic distribution: Properties and application. Asian Journal of Probability and Statistics, 1(3), 1-17.
Kemaloglu, S. A., & Yilmaz, M. (2017). Transmuted two-parameter Lindley distribution. Communications in Statistics-Theory and Methods, 46(23), 11866-11879.
Elbatal, I., & Muhammed, H. Z. (2014). Exponentiated generalized inverse Weibull distribution. Applied Mathematical Sciences, 8(81), 3997-4012.
data_Bcancer, data_bloodcancer
x<-data_bldercancer summary(x)x<-data_bldercancer summary(x)
The function allows to provide the lifetime (in years) of 40 blood cancer (leukemia) patients from one of Ministry of Health hospitals in Saudi Arabia.
data_bloodcancerdata_bloodcancer
data_bloodcancer |
A vector of (non-negative integer) values. |
This data consist of the lifetime (in years) of 40 blood cancer (leukemia) patients. Recently, the data set is used by Klakattawi, H. S. (2022) and fitted a new extended Weibull distribution.
data_bloodcancer gives the lifetime (in years) of 40 blood cancer (leukemia) patients.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Klakattawi, H. S. (2022). Survival analysis of cancer patients using a new extended Weibull distribution. Plos one, 17(2), e0264229.
Al-Saiary, Z. A., & Bakoban, R. A. (2020). The Topp-Leone generalized inverted exponential distribution with real data applications. Entropy, 22(10), 1144.
data_Bcancer, data_bloodcancer
x<-data_bloodcancer summary(x)x<-data_bloodcancer summary(x)
The function allows to provide the breakdown times (in minutes) of the electrical insulating fluid subject to a 30 KV voltage stress.
data_breakdowndata_breakdown
data_breakdown |
A vector of (non-negative integer) values. |
The data represent the breakdown times (in minutes) of the electrical insulating fluid subject to a 30 KV voltage stress. Recently, it is used by Tripathi. (2021) and fitted the inverse log-logistic distribution.
data_breakdown gives the breakdown times (in minutes) of the electrical insulating fluid subject.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Tripathi, H., Dey, S., & Saha, M. (2021). Double and group acceptance sampling plan for truncated life test based on inverse log-logistic distribution. Journal of Applied Statistics, 48(7), 1227-1242.
Lawless, J. F. (2011). Statistical models and methods for lifetime data. John Wiley & Sons.
x<-data_breakdown summary(x)x<-data_breakdown summary(x)
The function allows to provide the 100 breaking stress of carbon fibres (in Gba).
data_carfibresdata_carfibres
data_carfibres |
A vector of (non-negative integer) values. |
The data set consists of 100 breaking stress of carbon fibers (in Gba). Recently, it is used by Tripathi. (2021) and fitted the inverse log-logistic distribution.
data_carfibres gives the breaking stress of carbon fibers.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Tripathi, H., Dey, S., & Saha, M. (2021). Double and group acceptance sampling plan for truncated life test based on inverse log-logistic distribution. Journal of Applied Statistics, 48(7), 1227-1242.
Nichols, M. D., & Padgett, W. J. (2006). A bootstrap control chart for Weibull percentiles. Quality and reliability engineering international, 22(2), 141-151.
x<-data_carfibres summary(x)x<-data_carfibres summary(x)
The function allows to provide the incidence of 1,000 breast cancer patients within a period of 5 years starting from beginning of 2009 to end of 2013. The survival times for those patients were computed. Among them, 703 people were still alive at the end of 2013 and 55 patients had a zero lifetime and were believed to be wrongly reported or their records were absent upon death and thus excluded from the analysis. The remaining 242 patients have included.
data_brcancerdata_brcancer
data_brcancer |
A vector of (non-negative integer) values. |
The data represents the 242 breast cancer patients. Recently, it is used by Okasha and Matter (2015) and fitted the Burr type XII distribution.
data_brcancer gives the breast cancer patients.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Okasha, M. K., & Matter, M. Y. (2015). On the three-parameter Burr type XII distribution and its application to heavy tailed lifetime data. Journal: Journal of Advances in Mathematics, 10(4), 3429-3442.
x<-data_brcancer summary(x)x<-data_brcancer summary(x)
The function allows to provide 300 lifetime of the breast cancer patients reported by the UITH (University of Ilorin Teaching Hospital) of Nigeria.
data_breastcancerdata_breastcancer
data_breastcancer |
A vector of (non-negative integer) values. |
The data set consists of 300 lifetime of the breast cancer patients reported by the UITH (University of Ilorin Teaching Hospital) of Nige- ria. Recently, it is used by Shen et al. (2022) and fitted a new generalized rayleigh distribution.
data_breastcancer gives the lifetime of the breast cancer patients.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Shen, Z., Alrumayh, A., Ahmad, Z., Abu-Shanab, R., Al-Mutairi, M., & Aldallal, R. (2022). A new generalized rayleigh distribution with analysis to big data of an online community. Alexandria Engineering Journal, 61(12), 11523-11535.
Oguntunde, P. E., Adejumo, A. O., & Okagbue, H. I. (2017). Breast cancer patients in Nigeria: data exploration approach. Data in brief, 15, 47-57.
x<-data_breastcancer summary(x)x<-data_breastcancer summary(x)
The function allows to provide the survival times of 121 patients with breast cancer obtained from a large hospital in a period from 1929 to 1938.
data_breastcandata_breastcan
data_breastcan |
A vector of (non-negative integer) values. |
The data represents the 242 breast cancer patients. Recently, it is used by Tahir et al. (2014) and fitted the McDonald log-logistic distribution.
data_breastcan gives the survival times of 121 patients.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Tahir, M. H., Mansoor, M., Zubair, M., & Hamedani, G. (2014). McDonald log-logistic distribution with an application to breast cancer data. Journal of Statistical Theory and Applications.
Hamedani, G. (2013). The Zografos-Balakrishnan log-logistic distribution: Properties and applications. Journal of Statistical Theory and Applications.
Lee, E.T. (1992) Statistical Methods for Survival Data Analysis. John Wiley: New York.
x<-data_breastcan summary(x)x<-data_breastcan summary(x)
The function allows to provide the mortality rate of COVID-19 patients in Canada from 1 November to 26 December 2020.
data_mortalityCandata_mortalityCan
data_mortalityCan |
A vector of (non-negative integer) values. |
The data set represents the mortality rate of COVID-19 patients in Canada from 1 November to 26 December 2020. Recently, it is used by Almetwally (2022) and fitted the odd Weibull inverse Topp–Leone distribution.
data_mortalityCan gives the mortality rate of COVID-19 patients in Canada.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Almetwally, E. M. (2022). The odd Weibull inverse topp–leone distribution with applications to COVID-19 data. Annals of Data Science, 9(1), 121-140.
Nasiru, S., Abubakari, A. G., & Chesneau, C. (2022). New Lifetime Distribution for Modeling Data on the Unit Interval: Properties, Applications and Quantile Regression. Mathematical and Computational Applications, 27(6), 105.
data_COVIDDeath, data_COVIDfat, data_COVID19MH
x<-data_mortalityCan summary(x)x<-data_mortalityCan summary(x)
The function allows to provide a sample of 50 observed values of breaking stress of carbon fibers, the unit is Gba.
data_carbonfdata_carbonf
data_carbonf |
A vector of (non-negative integer) values. |
The data consists of a sample of 50 observed values of breaking stress of carbon fibers, the unit is Gba.
Recently, it is used by Alanzi et al. (2023) anda fitted a new Burr XII model based on the Bell-X functionalities.
data_carbonf gives the breaking stress of carbon fibers.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Almarashi, A. M., Khan, K., Chesneau, C., & Jamal, F. (2021). Group Acceptance Sampling Plan Using Marshall–Olkin Kumaraswamy Exponential (MOKw-E) Distribution. Processes, 9(6), 1066. Alanzi, A. R., Imran, M., Tahir, M. H., Chesneau, C., Jamal, F., Shakoor, S., & Sami, W. (2023). Simulation analysis, properties and applications on a new Burr XII model based on the Bell-X functionalities.
Fayomi, A., Tahir, M. H., Algarni, A., Imran, M., & Jamal, F. (2022). A new useful exponential model with applications to quality control and actuarial data. Computational Intelligence and Neuroscience, 2022.
Nichols, M. D., & Padgett, W. J. (2006). A bootstrap control chart for Weibull percentiles. Quality and reliability engineering international, 22(2), 141-151.
x<-data_carbonf summary(x)x<-data_carbonf summary(x)
The function allows to provide the survival times (in years) for the group of 46 patients given chemotherapy treatment.
data_chemotherapydata_chemotherapy
data_chemotherapy |
A vector of (non-negative integer) values. |
The data set relates to the survival times (in years) for the group of 46 patients given chemotherapy treatment. Recently, it is used by Nwezza and Ugwuowo(2022).
data_chemotherapy gives the survival times (in years) for the group of 46 patients given chemotherapy treatment.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Nwezza, E. E., & Ugwuowo, F. I. (2022). An extended normal distribution for reliability data analysis. Journal of Statistics and Management Systems, 25(2), 369-392.
Alizadeh, M., Tahir, M. H., Cordeiro, G. M., Mansoor, M., Zubair, M., & Hamedani, G. (2015). The Kumaraswamy marshal-Olkin family of distributions. Journal of the Egyptian Mathematical Society, 23(3), 546-557.
Bekker, A., Roux, J. J. J., & Mosteit, P. J. (2000). A generalization of the compound Rayleigh distribution: using a Bayesian method on cancer survival times. Communications in Statistics-Theory and Methods, 29(7), 1419-1433.
data_Bcancer, data_bldercancer
x<-data_chemotherapy summary(x)x<-data_chemotherapy summary(x)
The function allows to provide the intervals in days between 109 successive coal mining disasters in Great Britain during the period 1875-1951.
data_coalmindata_coalmin
data_coalmin |
A vector of (non-negative integer) values. |
The data represents the intervals in days between 109 successive coal mining disasters in Great Britain during the period 1875-1951. Recently, it is used by Bhatti et al. (2018) and fitted the modified Burr XII-inverse exponential distribution.
data_coalmin gives intervals in days between 109 successive coal mining disasters.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bhatti, F. A., Hamedani, G., Yousof, H. M., Ali, A., & Ahmad, M. (2018). On Modified Burr XII-Inverse Exponential Distribution: Properties, Characterizations and Applications. Journal of Biostatistics & Biometrics.
x<-data_coalmin summary(x)x<-data_coalmin summary(x)
The function allows to provide the time to failure in hours of an electronic component subjected to an accelerated life test.
data_electronicfdata_electronicf
data_electronicf |
A vector of (non-negative integer) values. |
The data represent the time to failure in hours of an electronic component subjected to an accelerated life test. Recently, it is used by Tripathi. (2021) and fitted the inverse log-logistic distribution.
data_electronicf gives the time to failure in hours of an electronic component.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Tripathi, H., Dey, S., & Saha, M. (2021). Double and group acceptance sampling plan for truncated life test based on inverse log-logistic distribution. Journal of Applied Statistics, 48(7), 1227-1242.
Montgomery, D. C. (2010). Managing, controlling, and improving quality. Wiley Global Education.
data_failureairc, data_windshieldf, data_breakdown
x<-data_electronicf summary(x)x<-data_electronicf summary(x)
The function allows to provide the incidence rate per every 10,000 inhabitants affected by COVID-19, with and without symptoms, in the first two months of the pandemic, these data were recorded starting on 2 March 2020.
data_COVID19Chiledata_COVID19Chile
data_COVID19Chile |
A vector of (non-negative integer) values. |
The data represents the incidence rate per every 10,000 inhabitants affected by COVID-19, with and without symptoms, in the first two months of the pandemic, these data were recorded starting on 2 March 2020. Recently, it is used by Santoro et al. (2022) and fitted the extended half-power exponential distribution.
data_COVID19Chile gives the incidence rate per every 10,000 inhabitants affected by COVID-19.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Santoro, K. I., Gómez, H. J., Barranco-Chamorro, I., & Gómez, H. W. (2022). Extended Half-Power Exponential Distribution with Applications to COVID-19 Data. Mathematics, 10(6), 942.
data_COVIDDeath, data_COVIDfat, data_COVIDmor, data_COVIDChile
x<-data_COVID19Chile summary(x)x<-data_COVID19Chile summary(x)
The function allows to provide the daily fatality confirmed cases attributable to COVID-19. The data consists of 89 observed values, with 18.72 reported deaths on average every day.
data_COVIDfatdata_COVIDfat
data_COVIDfat |
A vector of (non-negative integer) values. |
The data revealed the daily fatality confirmed cases attributable to COVID-19. The data consists of 89 observed values, with 18.72 reported deaths on average every day. Recently, the data set is used by Alyami et al.(2022) and fitted the Topp–Leone modified Weibull model.
data_COVIDfat gives the daily fatality confirmed cases attributable to COVID-19.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alyami, S. A., Elbatal, I., Alotaibi, N., Almetwally, E. M., Okasha, H. M., & Elgarhy, M. (2022). Topp–Leone Modified Weibull Model: Theory and Applications to Medical and Engineering Data. Applied Sciences, 12(20), 10431.
Abdullah Alahmadi, A., Alqawba, M., Almutiry, W., Shawki, A. W., Alrajhi, S., Al-Marzouki, S., & Elgarhy, M. (2022). A new version of weighted Weibull distribution: Modelling to COVID-19 data. Discrete Dynamics in Nature and Society, 2022.
data_COVIDDeath, data_COVID19MH, data_COVIDmor
x<-data_COVIDfat summary(x)x<-data_COVIDfat summary(x)
The function allows to provide mortality rate due to COVID-19 from 3 November 2021 to 11 November 2021 in France.
data_COVIDFrancedata_COVIDFrance
data_COVIDFrance |
A vector of (non-negative integer) values. |
The data set represents mortality rate due to COVID-19 from 3 November 2021 to 11 November 2021 in France. Recently, it is used by Almetwally et al. (2023) and fitted a unit-Weibull based on progressive type-II censored.
data_COVIDFrance gives the mortality rate due to COVID-19.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Almetwally, E. M., Jawa, T. M., Sayed-Ahmed, N., Park, C., Zakarya, M., & Dey, S. (2023). Analysis of unit-Weibull based on progressive type-II censored with optimal scheme. Alexandria Engineering Journal, 63, 321-338.
Moutinho Cordeiro, G., & dos Santos Brito, R. (2012). The beta power distribution.
data_COVID19MH, data_COVIDfat, data_COVIDmor
x<-data_COVIDFrance summary(x)x<-data_COVIDFrance summary(x)
The function allows to provide the mortality rate of the COVID-19 infected persons in Holland between March 31, 2020, and April 30, 2020.
data_COVID19MHdata_COVID19MH
data_COVID19MH |
A vector of (non-negative integer) values. |
The mortality rate of the COVID-19 infected persons in Holland between March 31, 2020, and April 30, 2020. Recently, it is used by Almongy et al. (2021) and fitted a new extended Rayleigh distribution.
data_COVID19Chile gives the mortality rate of the COVID-19 infected persons in Holland.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Zhou, Y., Ahmad, Z., Almaspoor, Z., Khan, F., Tag-Eldin, E., Iqbal, Z., & El-Morshedy, M. (2023). On the implementation of a new version of the Weibull distribution and machine learning approach to model the COVID-19 data. Mathematical biosciences and engineering: MBE, 20(1), 337-364.
Almongy, H. M., Almetwally, E. M., Aljohani, H. M., Alghamdi, A. S., & Hafez, E. H. (2021). A new extended Rayleigh distribution with applications of COVID-19 data. Results in Physics, 23, 104012.
data_COVIDDeath, data_COVIDfat, data_COVIDmor
x<-data_COVID19MH summary(x)x<-data_COVID19MH summary(x)
TThe function allows to provide a COVID-19 mortality rate belonging to Saudi Arabia of 32 days, which is recorded from 15 September 2020 to 16 October 2020.
data_COVIDmordata_COVIDmor
data_COVIDmor |
A vector of (non-negative integer) values. |
The data represent a COVID-19 mortality rate belonging to Saudi Arabia of 32 days, which is recorded from 15 September 2020 to 16 October 2020. Recently, it is used by Badr and Sobahi (2022) and fitted the exponentiated exponential-inverse Weibull model.
data_COVIDfat gives the COVID-19 mortality rate belonging to Saudi Arabia.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Badr, M. M., & Sobahi, G. (2022). The Exponentiated Exponential-Inverse Weibull Model: Theory and Application to COVID-19 Data in Saudi Arabia. Journal of Mathematics, 2022.
Almetwally, E. M. (2021). Extended odd weibull inverse Nadarajah-Haghighi distribution with application on COVID-19 in Saudi Arabia. Mathematical Sciences Letters, 10(3), 1-15.
data_COVIDDeath, data_COVIDfat, data_COVID19MH
x<-data_COVIDmor summary(x)x<-data_COVIDmor summary(x)
The function allows to provide the number of daily new deaths caused by COVID-19 in the UK from 15 February 2020 to 7 September 2021.
data_COVIDDeathdata_COVIDDeath
data_COVIDDeath |
A vector of (non-negative integer) values. |
The data set is the number of daily new deaths caused by COVID-19 in the UK from 15 February 2020 to 7 September 2021. Recently, it is used by Abbas et al. (2023) and fitted new extended Kumaraswamy exponential distribution.
data_COVIDDeath gives the daily new deaths caused by COVID-19 in the UK.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Abbas, S., Muhammad, M., Jamal, F., Chesneau, C., Muhammad, I., & Bouchane, M. (2023). A New Extension of the Kumaraswamy Generated Family of Distributions with Applications to Real Data. Computation, 11(2), 26.
data_COVID19MH, data_COVIDfat, data_COVIDmor
x<-data_COVIDDeath summary(x)x<-data_COVIDDeath summary(x)
The function allows to provide the recovery rates of COVID-19 patients in Spain from 3 March to 7 May 2020.
data_RRdata_RR
data_RR |
A vector of (non-negative integer) values. |
The data sets represent the recovery rates of COVID-19 patients in Spain from 3 March to 7 May 2020. Recently, it is used by Nasiru et al. (2022) and fitted the new lifetime distribution for modeling data on the unit interval.
data_RR gives the recovery rates of COVID-19 patients.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Nasiru, S., Abubakari, A. G., & Chesneau, C. (2022). New Lifetime Distribution for Modeling Data on the Unit Interval: Properties, Applications and Quantile Regression. Mathematical and Computational Applications, 27(6), 105.
Afify, A. Z., Nassar, M., Kumar, D., & Cordeiro, G. M. (2022). A new unit distribution: Properties, inference, and applications. Electronic Journal of Applied Statistical Analysis, 15(2), 460-484.
data_COVIDDeath, data_COVIDfat, data_COVIDmor
x<-data_RR summary(x)x<-data_RR summary(x)
The function allows to provide the failure time of cutting layers machine.
data_failuretcdata_failuretc
data_failuretc |
A vector of (non-negative integer) values. |
The failure time of cutting layers machine. Recently, it is used by Shah et al. (2022) and fitted a new member of the T-X family with applications in different sectors.
data_failuretc gives the failure time of cutting layers machine.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Shah, Z., Ali, A., Hamraz, M., Khan, D. M., Khan, Z., EL-Morshedy, M., & Almaspoor, Z. (2022). A New Member of TX Family with Applications in Different Sectors. Journal of Mathematics, 2022.
Algamal, Z. Y. (2008). Exponentiated exponential distribution as a failure time distribution. IRAQI Journal of Statistical science, 14, 63-75.
data_failureairc, data_electronicf
x<-data_failuretc summary(x)x<-data_failuretc summary(x)
The function allows to provide the times of breakdown of a sample of 25 devices at 180C.
data_breakdowntdata_breakdownt
data_breakdownt |
A vector of (non-negative integer) values. |
The data consist of the times of breakdown of a sample of 25 devices at 180C. Recently, it is used by Alotaibi et al. (2022) and fitted a new three-parameter inverse Weibull distribution.
data_breakdownt gives the breakdown times of devices.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alotaibi, R., Okasha, H., Rezk, H., & Nassar, M. (2023). A New Three-Parameter Inverse Weibull Distribution with Medical and Engineering Applications. CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 135(2), 1255-1274.
Pham, H. (2003). Handbook of reliability engineering (Vol. 1). H. Pham (Ed.). London: Springer.
x<-data_breakdownt summary(x)x<-data_breakdownt summary(x)
The function allows to provide the survival times (life lengths in years) until the onset of diabetes from a random sample of 105 patients obtained from the Bolgatanga Regional Hospital in the Upper East region of Ghana.
data_dpatientsdata_dpatients
data_dpatients |
A vector of (non-negative integer) values. |
The dataset represents the survival times (life lengths in years) until the onset of diabetes from a random sample of 105 patients obtained from the Bolgatanga Regional Hospital in the Upper East region of Ghana. Recently, it is used by Zamanah et al. (2022) and fitted the harmonic mixture Weibull-Weibull family of distributions.
data_dpatients gives the survival times (life lengths in years) until the onset of diabetes.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Zamanah, E., Nasiru, S., & Luguterah, A. (2022). Harmonic Mixture Weibull-G Family of Distributions: Properties, Regression and Applications to Medical Data. Computational and Mathematical Methods, 2022.
x<-data_dpatients summary(x)x<-data_dpatients summary(x)
The function allows to provide the 50 observations of holes having a diameter of 12mm and a thickness of the sheet of 3.15mm.
data_drillingdata_drilling
data_drilling |
A vector of (non-negative integer) values. |
The data set is based on 50 observations of holes having a diameter of 12mm and a thickness of the sheet of 3.15mm. Recently, it is used by Alanzi et al. (2022) and fitted a new modified Kumaraswamy distribution.
data_drilling gives the data of holes having a diameter of 12mm and a thickness of the sheet of 3.15mm.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alanzi, A. R., Rafique, M. Q., Tahir, M. H., Sami, W., & Jamal, F. (2022). A New Modified Kumaraswamy Distribution: Actuarial Measures and Applications. Journal of Mathematics, 2022.
Dasgupta, R. (2011). On the distribution of burr with applications. Sankhya B, 73, 1-19.
x<-data_drilling summary(x)x<-data_drilling summary(x)
The function allows to provide the Ethereum exchange rates data set.
data_Ethereumerdata_Ethereumer
data_Ethereumer |
A vector of (non-negative integer) values. |
The Ethereum exchange rates data set. Recently, it is used by Wang et al. (2023) and fitted a new Dagum model.
data_Ethereumer gives the Ethereum exchange rates.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Wang, Y., Ahmad, Z., Khan, F., Alnagar, D. K., Alsuhabi, H., Alkhairy, I., & Yusuf, M. (2023). Analysis of cryptocurrency exchange rates vs USA dollars using a new Dagum model. Alexandria Engineering Journal, 64, 645-658.
x<-data_Ethereumer summary(x)x<-data_Ethereumer summary(x)
The function allows to provide the failure and run times from a sample of 30 devices.
data_runtimesdata_runtimes
data_runtimes |
A vector of (non-negative integer) values. |
The values are the failure and run times from a sample of 30 devices. Recently, it is used by Abbas et al. (2023) and fitted new extended Kumaraswamy exponential distribution.
data_runtimes gives the failure and run times from a sample of 30 devices.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Abbas, S., Muhammad, M., Jamal, F., Chesneau, C., Muhammad, I., & Bouchane, M. (2023). A New Extension of the Kumaraswamy Generated Family of Distributions with Applications to Real Data. Computation, 11(2), 26.
William, Q. M., & Escobar, L. A. (1998). Statistical methods for reliability data. A. Wiley Interscience Publications, 639.
data_breakdown, data_breakdownt, data_failureairc
x<-data_runtimes summary(x)x<-data_runtimes summary(x)
The function allows to provide the failure times of 84 aircraft windshield.
data_windshieldfdata_windshieldf
data_windshieldf |
A vector of (non-negative integer) values. |
The data refer to the failure times of 84 aircraft windshields. Recently, it is used by Tahir et al. (2015) and fitted the Weibull-Lomax distribution.
data_windshieldf gives the failure times of 84 aircraft windshields.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Tahir, M. H., Cordeiro, G. M., Mansoor, M., & Zubair, M. (2015). The Weibull-Lomax distribution: properties and applications. Hacettepe Journal of Mathematics and Statistics, 44(2), 455-474.
data_breakdown, data_breakdownt, data_failureairc
x<-data_windshieldf summary(x)x<-data_windshieldf summary(x)
The function allows to provide the time between failures for repairable 30 items.
data_repairabledata_repairable
data_repairable |
A vector of (non-negative integer) values. |
The data refer to the time between failures for repairable 30 items. Recently, it is used by Cordeiro et al. (2016) and fitted an extended Birnbaum–Saunders distribution.
data_repairable gives the time between failures for repairable 30 items.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Cordeiro, G. M., Lima, M. D. C. S., Cysneiros, A. H., Pascoa, M. A., Pescim, R. R., & Ortega, E. M. (2016). An extended Birnbaum–Saunders distribution: Theory, estimation, and applications. Communications in Statistics-Theory and Methods, 45(8), 2268-2297.
Murthy, D.N.P., Xie, M., Jiang, R. (2004). Weibull Models. Hoboken, NJ: John Wiley.
data_breakdown, data_breakdownt, data_failureairc
x<-data_repairable summary(x)x<-data_repairable summary(x)
TThe function allows to provide the COVID-19 fatality rates in Saudi Arabia. These measurements were taken over 37 days, beginning on June 27 and ending on August 2, 2021.
data_morCOVIDdata_morCOVID
data_morCOVID |
A vector of (non-negative integer) values. |
The data consists of the COVID-19 fatality rates in Saudi Arabia. These measurements were taken over 37 days, beginning on June 27 and ending on August 2, 2021. Recently, it is used by Alshanbari et al. (2022) and fitted the novel type I half-logistic Burr-Weibull distribution.
data_morCOVID gives the COVID-19 fatality rates in Saudi Arabia.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alshanbari, H. M., Odhah, O. H., Almetwally, E. M., Hussam, E., Kilai, M., & El-Bagoury, A. A. H. (2022). Novel Type I Half Logistic Burr-Weibull Distribution: Application to COVID-19 Data. Computational and Mathematical Methods in Medicine, 2022.
data_COVIDDeath, data_COVIDfat, data_COVID19MH
x<-data_morCOVID summary(x)x<-data_morCOVID summary(x)
The function allows to provide the COVID-19 fatality rates in Saudi Arabia. These measurements were taken over 37 days, beginning on June 27 and ending on August 2, 2021.
data_fatCOVIDdata_fatCOVID
data_fatCOVID |
A vector of (non-negative integer) values. |
The data consists of the COVID-19 fatality rates in Saudi Arabia. These measurements were taken for 37 days, beginning on June 27 and ending on August 2, 2021. Recently, it is used by Alshanbari et al. (2022) and fitted the novel type I half-logistic Burr-Weibull distribution.
data_fatCOVID gives the COVID-19 fatality rates in Saudi Arabia.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alshanbari, H. M., Odhah, O. H., Almetwally, E. M., Hussam, E., Kilai, M., & El-Bagoury, A. A. H. (2022). Novel Type I Half Logistic Burr-Weibull Distribution: Application to COVID-19 Data. Computational and Mathematical Methods in Medicine, 2022.
data_COVIDDeath, data_COVID19MH, data_COVIDmor
x<-data_fatCOVID summary(x)x<-data_fatCOVID summary(x)
The function allows to provide the maximum annual flood discharges (in units of 1000 cubic feet per second) of the North Saskachevan River at Edmonton, over 48 years.
data_flooddata_flood
data_flood |
A vector of (non-negative integer) values. |
The data represent the maximum annual flood discharges (in units of 1000 cubic feet per second) of the North Saskachevan River at Edmonton, over 48 years. Recently, it is used by Tahir et al. (2020) and fitted the new Kumaraswamy-Weibull (NKwW) distribution.
data_flood gives the the maximum annual flood discharges.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Tahir, M. H., Hussain, M. A., Cordeiro, G. M., El-Morshedy, M., & Eliwa, M. S. (2020). A new Kumaraswamy generalized family of distributions with properties, applications, and bivariate extension. Mathematics, 8(11), 1989.
Asgharzadeh, A., Bakouch, H. S., & Habibi, M. (2017). A generalized binomial exponential 2 distribution: modeling and applications to hydrologic events. Journal of Applied Statistics, 44(13), 2368-2387.
data_floodSus, data_floodtime, data_floodpeak,
x<-data_flood summary(x)x<-data_flood summary(x)
The function allows to provide the 72 excrescences of flood peaks for the years 1958–1984 (rounded to one decimal place) of flood peaks (in m3 per s) of the Wheaton River near Carcross in Yukon Territory, Canada.
data_floodpeakdata_floodpeak
data_floodpeak |
A vector of (non-negative integer) values. |
This data set represents 72 excrescences of flood peaks for the years 1958–1984 (rounded to one decimal place) of flood peaks (in m3 per s) of the Wheaton River near Carcross in Yukon Territory, Canada. Recently, it is used by Mohamed et al. (2022) and fitted a Marshall-Olkin extended Gompertz Makeham model.
data_floodpeak gives the 72 excrescences of flood peaks for the years 1958–1984.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Mohamed, R. A., Al-Babtain, A. A., Elbatal, I., Almetwally, E. M., & Almongy, H. M. (2022). Classical and Bayesian Inference of Marshall-Olkin Extended Gompertz Makeham Model with Modeling of Physics Data. Journal of Mathematics, 2022.
data_floodSus, data_flood, data_floodtime
x<-data_floodpeak summary(x)x<-data_floodpeak summary(x)
The function allows to provide the food and drink wholesaling in the United Kingdom from 2000 to 2019 as one factor of FTP.
data_wholesaledata_wholesale
data_wholesale |
A vector of (non-negative integer) values. |
The data set represents the food and drink wholesaling in the United Kingdom from 2000 to 2019 as one factor of FTP. Recently, it is used by Alyami et al. (2022) and fitted the sine-exponentiated Weibull exponential (SEWEx), the sine-exponentiated Weibull Rayleigh (SEWR) and sine-exponentiated Weibull Burr X (SEWBX) distributions.
data_wholesale gives the food and drink wholesaling in the United Kingdom.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alyami, S. A., Elbatal, I., Alotaibi, N., Almetwally, E. M., & Elgarhy, M. (2022). Modeling to Factor Productivity of the United Kingdom Food Chain: Using a New Lifetime Generated Family of Distributions. Sustainability, 14(14), 8942.
x<-data_wholesale summary(x)x<-data_wholesale summary(x)
The function allows to provide the food chain in the United Kingdom from 2000 to 2019.
data_foodchaindata_foodchain
data_foodchain |
A vector of (non-negative integer) values. |
The dataset represents the food chain in the United Kingdom from 2000 to 2019. Recently, it is used by Alyami et al. (2022) and fitted the sine-exponentiated Weibull exponential (SEWEx), the sine-exponentiated Weibull Rayleigh (SEWR) and sine-exponentiated Weibull Burr X (SEWBX) distributions.
data_foodchain gives the food chain in the United Kingdom from 2000 to 2019.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alyami, S. A., Elbatal, I., Alotaibi, N., Almetwally, E. M., & Elgarhy, M. (2022). Modeling to Factor Productivity of the United Kingdom Food Chain: Using a New Lifetime Generated Family of Distributions. Sustainability, 14(14), 8942.
x<-data_foodchain summary(x)x<-data_foodchain summary(x)
The function allows to provide the fracture toughness MPa m1/2 data from the material Alumina.
data_fracturedata_fracture
data_fracture |
A vector of (non-negative integer) values. |
The data represents the fracture toughness MPa m1/2 data from the material Alumina. Recently, it is used by Bhatti et al. (2018) and fitted the modified Burr XII-inverse exponential distribution.
data_fracture gives the fracture toughness MPa m1/2 data from the material Alumina.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bhatti, F. A., Hamedani, G., Yousof, H. M., Ali, A., & Ahmad, M. (2018). On Modified Burr XII-Inverse Exponential Distribution: Properties, Characterizations and Applications. Journal of Biostatistics & Biometrics.
x<-data_fracture summary(x)x<-data_fracture summary(x)
The function allows to provide the survival times (in days) of 72 guinea pigs infected with virulent tubercle bacilli.
data_guineapigsdata_guineapigs
data_guineapigs |
A vector of (non-negative integer) values. |
The data set represents the survival times (in days) of 72 guinea pigs infected with virulent tubercle bacilli. Recently, the data set is used by Alyami et al.(2022) and fitted the Topp–Leone modified Weibull model.
data_guineapigs gives the survival times (in days) of 72 guinea pigs.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bjerkedal, T. (1960). Acquisition of Resistance in Guinea Pies infected with Different Doses of Virulent Tubercle Bacilli. American Journal of Hygiene, 72(1), 130-48.
Chesneau, C., & El Achi, T. (2020). Modified odd Weibull family of distributions: Properties and applications. Journal of the Indian Society for Probability and Statistics, 21, 259-286.
Khosa, S. K., Afify, A. Z., Ahmad, Z., Zichuan, M., Hussain, S., & Iftikhar, A. (2020). A new extended-f family: properties and applications to lifetime data. Journal of Mathematics, 2020, 1-9.
Alyami, S. A., Elbatal, I., Alotaibi, N., Almetwally, E. M., Okasha, H. M., & Elgarhy, M. (2022). Topp–Leone Modified Weibull Model: Theory and Applications to Medical and Engineering Data. Applied Sciences, 12(20), 10431.
Kemaloglu, S. A., & Yilmaz, M. (2017). Transmuted two-parameter Lindley distribution. Communications in Statistics-Theory and Methods, 46(23), 11866-11879.
data_analgesic, data_dpatients
x<-data_guineapigs summary(x)x<-data_guineapigs summary(x)
The function allows to provide the survival time for 44 patients diagnosed with Head and Neck cancer disease.
data_hdneckcancerdata_hdneckcancer
data_hdneckcancer |
A vector of (non-negative integer) values. |
Survival time for 44 patients diagnosed with head and neck cancer disease. Recently, the data set is used by Klakattawi, H. S. (2022) and fitted a new extended Weibull distribution.
data_hdneckcancer gives the survival time for 44 patients diagnosed with Head and Neck cancer disease.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Klakattawi, H. S. (2022). Survival analysis of cancer patients using a new extended Weibull distribution. Plos one, 17(2), e0264229.
Cordeiro, G. M., Ortega, E. M., & da Cunha, D. C. (2013). The exponentiated generalized class of distributions. Journal of data science, 11(1), 1-27.
data_Bcancer, data_bloodcancer
x<-data_hdneckcancer summary(x)x<-data_hdneckcancer summary(x)
The function allows to provide of average annual percent change in private health insurance premiums.
data_healthinsurdata_healthinsur
data_healthinsur |
A vector of (non-negative integer) values. |
The data set represents of average annual percent change in private health insurance premiums. Recently, it is used by Mukhtar et al. (2019) and fitted the c-Donald modified Burr-III distribution.
data_healthinsur gives the average annual percent change in private health insurance premiums.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Mukhtar, S., Ali, A., & Alya, A. M. (2019). Mc-Donald modified Burr-III distribution: properties and applications. Journal of Taibah University for Science, 13(1), 184-192.
Kibria, B. G., & Shakil, M. (2011). A new five-parameter Burr system of distributions based on generalized Pearson differential equation. Proceedings, Section on Physical and Engineering Sciences.
x<-data_healthinsur summary(x)x<-data_healthinsur summary(x)
TThe function allows to provide the 50 observations of holes having a diameter of 9mm and a thickness of the sheet of 2mm.
data_drillinghdata_drillingh
data_drillingh |
A vector of (non-negative integer) values. |
The dataset is based on 50 observations of holes having a diameter of 9mm and a thickness of the sheet of 2mm. Recently, it is used by Alanzi et al. (2022) and fitted a new modified Kumaraswamy distribution.
data_drillingh gives the data of holes having a diameter of 9mm and a thickness of the sheet of 2mm.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alanzi, A. R., Rafique, M. Q., Tahir, M. H., Sami, W., & Jamal, F. (2022). A New Modified Kumaraswamy Distribution: Actuarial Measures and Applications. Journal of Mathematics, 2022.
Dasgupta, R. (2011). On the distribution of burr with applications. Sankhya B, 73, 1-19.
x<-data_drillingh summary(x)x<-data_drillingh summary(x)
The function allows to provide the survival times (life lengths in years) until the onset of hypertension from a random sample of 119 patients obtained from the Bolgatanga Regional Hospital in the Upper East region of Ghana.
data_hpatientsdata_hpatients
data_hpatients |
A vector of (non-negative integer) values. |
The data set represents the survival times (life lengths in years) until the onset of hypertension from a random sample of 119 patients obtained from the Bolgatanga Regional Hospital in the Upper East region of Ghana. Recently, it is used by Zamanah et al. (2022) and fitted the harmonic mixture Weibull-Weibull family of distributions.
data_hpatients gives the survival times (life lengths in years) until the onset of hypertension.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Zamanah, E., Nasiru, S., & Luguterah, A. (2022). Harmonic Mixture Weibull-G Family of Distributions: Properties, Regression and Applications to Medical Data. Computational and Mathematical Methods, 2022.
x<-data_hpatients summary(x)x<-data_hpatients summary(x)
The function allows to provide the image of Foulum (Denmark) obtained by the EMISAR sensor, jointly built by the ElectroMagnetics Institute (EMI), the Technical University of Denmark (TUD), and its Danish Centre for Remote Sensing (DCRS), operated at C- and L-bands (though not simultaneously) with quad-polarizations.
data_imagedata_image
data_image |
A vector of (non-negative integer) values. |
The database extracted from an image of Foulum (Denmark) obtained by the EMISAR sensor, jointly built by the ElectroMagnetics Institute (EMI), the Technical University of Denmark (TUD), and its Danish Centre for Remote Sensing (DCRS), operated at C- and L-bands (though not simultaneously) with quad-polarizations. Recently, it is used by Alizadeh et al. (2017) and fitted the odd-Burr normal distribution.
data_image gives the image of Foulum (Denmark) obtained by the EMISAR sensor.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alizadeh, M., Cordeiro, G. M., Nascimento, A. D., Lima, M. D. C. S., & Ortega, E. M. (2017). Odd-Burr generalized family of distributions with some applications. Journal of statistical computation and simulation, 87(2), 367-389.
x<-data_image summary(x)x<-data_image summary(x)
The function allows to provide the COVID-19 incidence rate per 10,000 inhabitants affected by the virus without symptoms during the second quarter of 2020.
data_COVIDChiledata_COVIDChile
data_COVIDChile |
A vector of (non-negative integer) values. |
A real dataset related to COVID-19 in Chile, the data represent the incidence rate per 10,000 inhabitants affected by the virus without symptoms during the second quarter of 2020. Recently, it is used by Santoro et al. (2022) and fitted the extended half-power exponential distribution.
data_COVIDChile gives the incidence rate per 10,000 inhabitants affected by the virus without symptoms.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Santoro, K. I., Gómez, H. J., Barranco-Chamorro, I., & Gómez, H. W. (2022). Extended Half-Power Exponential Distribution with Applications to COVID-19 Data. Mathematics, 10(6), 942.
data_COVIDDeath, data_COVIDfat, data_COVIDmor
x<-data_COVIDChile summary(x)x<-data_COVIDChile summary(x)
The function allows to provide the minimum insurance claim for every six month period from the 3rd of January 1980 to the 31 of December of 1990.
data_insurclaimdata_insurclaim
data_insurclaim |
A vector of (non-negative integer) values. |
The data represents the minimum insurance claim for every six month period from the 3rd of January 1980 to the 31 of December of 1990. Recently, it is used by Asgharzadeh et al. (2014) and fitted the Burr Poisson–Lindley distribution.
data_insurclaim gives the minimum insurance claim for every six month.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Asgharzadeh, A., Bakouch, H. S., Nadarajah, S., & Esmaeili, L. (2014). A new family of compound lifetime distributions. Kybernetika, 50(1), 142-169.
data_vehicleinsur, data_healthinsur
x<-data_insurclaim summary(x)x<-data_insurclaim summary(x)
The function allows to provide the times to infection of kidney dialysis patients in months.
data_kidneydata_kidney
data_kidney |
A vector of (non-negative integer) values. |
The data set consists of times to infection of kidney dialysis patients in months. Recently, it is used by Bantan et al. (2020) and fitted the unit-Rayleigh distribution.
data_kidney gives the times to infection of kidney dialysis patients in months.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bantan, R. A., Chesneau, C., Jamal, F., Elgarhy, M., Tahir, M. H., Ali, A., ... & Anam, S. (2020). Some new facts about the unit-Rayleigh distribution with applications. Mathematics, 8(11), 1954.
Klein, J. P., & Moeschberger, M. L. (2003). Survival analysis: techniques for censored and truncated data (Vol. 1230). New York: Springer.
x<-data_kidney summary(x)x<-data_kidney summary(x)
The function allows to provide the unit intervel data set consists of times to infection of kidney dialysis patients in months.
data_kidneyunitdata_kidneyunit
data_kidneyunit |
A vector of (non-negative integer) values. |
The unit intervel data set consists of times to infection of kidney dialysis patients in months. Recently, it is used by Bantan et al. (2020) and fitted the unit-Rayleigh distribution.
data_kidneyunit gives the times to infection of kidney dialysis patients in months.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bantan, R. A., Chesneau, C., Jamal, F., Elgarhy, M., Tahir, M. H., Ali, A., ... & Anam, S. (2020). Some new facts about the unit-Rayleigh distribution with applications. Mathematics, 8(11), 1954.
Klein, J. P., & Moeschberger, M. L. (2003). Survival analysis: techniques for censored and truncated data (Vol. 1230). New York: Springer.
x<-data_kidneyunit summary(x)x<-data_kidneyunit summary(x)
The function allows to provide the 128 plants which are measures of the phosphorus concentration in the leaves.
data_leavesdata_leaves
data_leaves |
A vector of (non-negative integer) values. |
The data describe the 128 plants which are measures of the phosphorus concentration in the leaves. Recently, it is used by Silva et al. (2015) and fitted The compound class of extended Weibull power series distributions.
data_leaves gives the phosphorus concentration in the leaves.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Silva, R. B., Bourguignon, M., Dias, C. R., & Cordeiro, G. M. (2013). The compound class of extended Weibull power series distributions. Computational Statistics & Data Analysis, 58, 352-367.
x<-data_leaves summary(x)x<-data_leaves summary(x)
The function allows to provide the survival times (days) of 40 patients suffering from leukemia.
data_leukemiadata_leukemia
data_leukemia |
A vector of (non-negative integer) values. |
The data consists of the survival times (days) of 40 patients suffering from leukemia. Recently, the data set is used by Bhatti et al. (2019) and fitted the Burr III-Marshal Olkin-Weibull distribution.
data_leukemia gives the survival times (days) of 40 patients suffering from leukemia.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bhatti, F. A., Hamedani, G. G., Korkmaz, M. C., Cordeiro, G. M., Yousof, H. M., & Ahmad, M. (2019). On Burr III Marshal Olkin family: development, properties, characterizations and applications. Journal of Statistical Distributions and Applications, 6, 1-21.
Elbatal, I., & Muhammed, H. Z. (2014). Exponentiated generalized inverse Weibull distribution. Applied Mathematical Sciences, 8(81), 3997-4012.
Kemaloglu, S. A., & Yilmaz, M. (2017). Transmuted two-parameter Lindley distribution. Communications in Statistics-Theory and Methods, 46(23), 11866-11879.
data_Bcancer, data_bloodcancer
x<-data_leukemia summary(x)x<-data_leukemia summary(x)
The function allows to provide the maximum flood level for the Susquehanna River at Harrisburg, Pennsylvania.
data_floodSusdata_floodSus
data_floodSus |
A vector of (non-negative integer) values. |
The maximum flood level for the Susquehanna River at Harrisburg, Pennsylvania. Recently, it is used by Marinho (2016).
data_floodSus gives the maximum flood level for the Susquehanna River.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Marinho, P. R. D., Bourguignon, M., & Marinho, M. P. R. D. (2016). Package ‘AdequacyModel’.
Dumonceaux, R., Antle, C. E., & Haas, G. (1973). Likelihood ratio test for discriminagon between two models with unknown location and scale parameters. Technometrics, 15(1), 19-27.
data_flood, data_floodtime, data_floodpeak,
x<-data_floodSus summary(x)x<-data_floodSus summary(x)
The function allows to provide the COVID-19 mortality rate data belonging to Mexico of 108 days, which is recorded from 4 March to 20 July 2020.
data_MorRdata_MorR
data_MorR |
A vector of (non-negative integer) values. |
The data represents a COVID-19 mortality rate data belonging to Mexico of 108 days, which is recorded from 4 March to 20 July 2020. Recently, it is used by Almongy et al. (2021) and fitted a new extended Rayleigh distribution.
data_MorR gives the COVID-19 mortality rate data belonging to Mexico.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Almongy, H. M., Almetwally, E. M., Aljohani, H. M., Alghamdi, A. S., & Hafez, E. H. (2021). A new extended Rayleigh distribution with applications of COVID-19 data. Results in Physics, 23, 104012.
data_COVIDDeath, data_COVIDfat, data_COVID19MH
x<-data_MorR summary(x)x<-data_MorR summary(x)
The function allows to provide the overall yield production of 107 cows at the first birth of the SINDI race.
data_Milkpdata_Milkp
data_Milkp |
A vector of (non-negative integer) values. |
The data revealed the overall yield production of 107 cows at the first birth of the SINDI race. Recently, it is used by Alanzi et al. (2022) and fitted a new modified Kumaraswamy distribution.
data_Milkp gives the overall yield production of 107 cows at the first birth.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alanzi, A. R., Rafique, M. Q., Tahir, M. H., Sami, W., & Jamal, F. (2022). A New Modified Kumaraswamy Distribution: Actuarial Measures and Applications. Journal of Mathematics, 2022.
Moutinho Cordeiro, G., & dos Santos Brito, R. (2012). The beta power distribution.
x<-data_Milkp summary(x)x<-data_Milkp summary(x)
The function allows to provide the natural increase rates for the period from 1951 to 2010. The rate of natural increase is calculated as difference of the crude birth rate and the crude death rate of a population.
data_increaseratedata_increaserate
data_increaserate |
A vector of (non-negative integer) values. |
The data set consists of natural increase rates for the period from 1951 to 2010. The rate of natural increase is calculated as difference of the crude birth rate and the crude death rate of a population. Recently, it is used by Ristić et al. (2015) and fitted the generalized beta exponential distribution.
data_increaserate gives the natural increase rates for the period from 1951 to 2010.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Ristić, M. M., Popović, B. V., & Nadarajah, S. (2015). Libby and Novick's generalized beta exponential distribution. Journal of Statistical Computation and Simulation, 85(4), 740-761.
x<-data_increaserate summary(x)x<-data_increaserate summary(x)
The function allows to provide the unemployment claims from July 2008 to April, reported by the Department of Labour, Licencing, and Regulation, USA.
data_insurundata_insurun
data_insurun |
A vector of (non-negative integer) values. |
The data set represents the unemployment claims from July 2008 to April, reported by the Department of Labour, Licencing, and Regulation, USA. Recently, it is used by Fayomi et al. (2022) and fitted a new useful exponential model.
data_insurun gives the unemployment claims from July 2008 to April.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Fayomi, A., Tahir, M. H., Algarni, A., Imran, M., & Jamal, F. (2022). A new useful exponential model with applications to quality control and actuarial data. Computational Intelligence and Neuroscience, 2022.
x<-data_insurun summary(x)x<-data_insurun summary(x)
The function allows to provide the computation time of P3 algorithms.
data_P3data_P3
data_P3 |
A vector of (non-negative integer) values. |
The data providing computation time of P3 algorithms. Recently, it is used by Bantan et al. (2022) and fitted using a new univariate and bivariate statistical model.
data_P3 gives the computation time of P3 algorithms.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bantan, R. A., Shafiq, S., Tahir, M. H., Elhassanein, A., Jamal, F., Almutiry, W., & Elgarhy, M. (2022). Statistical Analysis of COVID-19 Data: Using A New Univariate and Bivariate Statistical Model. Journal of Function Spaces, 2022.
Biswas, A., & Chakraborty, S. (2021). A new method for constructing continuous distributions on the unit interval. arXiv preprint arXiv:2101.04661.
x<-data_P3 summary(x)x<-data_P3 summary(x)
The function allows to provide the lifetime's data relating to relief times (in minutes) for 20 patients receiving an analgesic.
data_analgesicdata_analgesic
data_analgesic |
A vector of (non-negative integer) values. |
The data set represents the lifetime's data relating to relief times (in minutes) for 20 patients receiving an analgesic. Recently, it is used by Peter et al. (2021) and fitted the Gamma odd Burr III-G family of distributions.
data_analgesic gives the relief times (in minutes).
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Peter, P. O., Oluyede, B., Bindele, H. F., Ndwapi, N., & Mabikwa, O. (2021). The Gamma Odd Burr III-G Family of Distributions: Model, Properties and Applications. Revista Colombiana de Estadística, 44(2), 331-368.
Gross, A. J., & Clark, V. A. (1975). Survival distributions: reliability applications in the biomedical sciences (Vol. 11). New York: Wiley.
x<-data_analgesic summary(x)x<-data_analgesic summary(x)
The function allows to provide the permeability measured in millidarcies, only the shallow permeability values are presented.
data_permeabilitydata_permeability
data_permeability |
A vector of (non-negative integer) values. |
The data presents the permeability measured in millidarcies, only the shallow permeability values are presented. Recently, it is used by Ricciardi et al. (2005) and fitted the beta generalized inverted exponential distribution.
data_permeability gives the permeability measured in millidarcies.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Ricciardi, K. L., Pinder, G. F., & Belitz, K. (2005). Comparison of the lognormal and beta distribution functions to describe the uncertainty in permeability. Journal of Hydrology, 313(3-4), 248-256.
Law, J. (1944). A statistical approach to the interstitial heterogeneity of sand reservoirs. Transactions of the AIME, 155(01), 202-222.
x<-data_permeability summary(x)x<-data_permeability summary(x)
The function allows to provide the petroleum rock samples from a petroleum reservoir.
data_petroleumdata_petroleum
data_petroleum |
A vector of (non-negative integer) values. |
The data set represents the petroleum rock samples from a petroleum reservoir. Recently, it is used by ZeinEldin et al. (2020) and fitted a Type II half logistic Kumaraswamy distribution.
data_petroleum gives the petroleum rock samples from a petroleum reservoir.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
ZeinEldin, R. A., Haq, M. A. U., Hashmi, S., Elsehety, M., & Elgarhy, M. (2020). Type II half logistic Kumaraswamy distribution with applications. Journal of Function Spaces, 2020, 1-15.
Moutinho Cordeiro, G., & dos Santos Brito, R. (2012). The beta power distribution.
x<-data_petroleum summary(x)x<-data_petroleum summary(x)
The function allows to provide the strength lifetime for a glass airplane window.
data_airplanewindata_airplanewin
data_airplanewin |
A vector of (non-negative integer) values. |
The data represents the strength lifetime for a glass airplane window. Recently, it is used by Bakoban and Zinadah (2017) and fitted the beta generalized inverted exponential distribution.
data_airplanewin gives the lifetime for a glass airplane window.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bakoban, R. A., & Abu-Zinadah, H. H. (2017). The beta generalized inverted exponential distribution with real data applications. REVSTAT-Statistical Journal, 15(1), 65-88.
Fuller Jr, E. R., Freiman, S. W., Quinn, J. B., Quinn, G. D., & Carter, W. C. (1994, September). Fracture mechanics approach to the design of glass aircraft windows: A case study. In Window and dome technologies and materials IV (Vol. 2286, pp. 419-430). SPIE.
x<-data_airplanewin summary(x)x<-data_airplanewin summary(x)
The function allows to provide the annual maximum precipitation (inches) for one rain gauge in Fort Collins, Colorado from 1900 through 1999.
data_precipitationdata_precipitation
data_precipitation |
A vector of (non-negative integer) values. |
The data represents the annual maximum precipitation (inches) for one rain gauge in Fort Collins, Colorado from 1900 through 1999. Recently, it is used by Tahir et al. (2020) and fitted the new Kumaraswamy-Weibull distribution.
data_precipitation gives the annual maximum precipitation (inches).
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Tahir, M. H., Hussain, M. A., Cordeiro, G. M., El-Morshedy, M., & Eliwa, M. S. (2020). A new Kumaraswamy generalized family of distributions with properties, applications, and bivariate extension. Mathematics, 8(11), 1989.
Katz, R. W., Parlange, M. B., & Naveau, P. (2002). Statistics of extremes in hydrology. Advances in water resources, 25(8-12), 1287-1304.
x<-data_precipitation summary(x)x<-data_precipitation summary(x)
The function allows to provide the 150 observations and is related to the Reddit advertising.
data_redditdata_reddit
data_reddit |
A vector of (non-negative integer) values. |
The data set consists of 150 observations and is related to the Reddit advertising. Recently, it is used by Shen et al. (2022) and fitted a new generalized rayleigh distribution.
data_reddit gives the 150 observations and is related to the Reddit advertising.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Shen, Z., Alrumayh, A., Ahmad, Z., Abu-Shanab, R., Al-Mutairi, M., & Aldallal, R. (2022). A new generalized rayleigh distribution with analysis to big data of an online community. Alexandria Engineering Journal, 61(12), 11523-11535.
x<-data_reddit summary(x)x<-data_reddit summary(x)
The function allows to provide the relief times of 20 patients who are receiving an analgesic.
data_relieftimedata_relieftime
data_relieftime |
A vector of (non-negative integer) values. |
The dataset represents the relief times of 20 patients who are receiving an analgesic. Recently, it is used by Afify et al. (2021) and fitted a new two-parameter burr-hatke distribution.
data_relieftime gives the relief times of 20 patients who are receiving an analgesic.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Afify, A. Z., Aljohani, H. M., Alghamdi, A. S., Gemeay, A. M., & Sarg, A. M. (2021). A new two-parameter burr-hatke distribution: Properties and bayesian and non-bayesian inference with applications. Journal of Mathematics, 2021, 1-16.
Gross, A. J., & Clark, V. A. (1975). Survival distributions: reliability applications in the biomedical sciences (Vol. 11). New York: Wiley.
x<-data_relieftime summary(x)x<-data_relieftime summary(x)
The function allows to provide the remission time of 128 bladder cancer patients.
data_Bcancerdata_Bcancer
data_Bcancer |
A vector of (non-negative integer) values. |
The data set consists of the remission time of 128 bladder cancer patients. Recently, it is used by Ijaz et al. (2020) and fitted a Gull alpha power Weibull distribution.
data_Bcancer gives the remission time of 128 bladder cancer patients.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Ijaz, M., Asim, S. M., Farooq, M., Khan, S. A., & Manzoor, S. (2020). A Gull Alpha Power Weibull distribution with applications to real and simulated data. Plos one, 15(6), e0233080.
Aldeni M., Lee C., & Famoye F. (2017). Families of distributions arising from the quantile of generalized lambda distribution. Journal of Statistical Distributions and Applications, 4(1), 25.
data_Bcancer, data_bloodcancer
x<-data_Bcancer summary(x)x<-data_Bcancer summary(x)
The function allows to provide the computation time of SC16 algorithms.
data_SC16data_SC16
data_SC16 |
A vector of (non-negative integer) values. |
The data providing computation time of SC16 algorithms. Recently, it is used by Bantan et al. (2022) and fitted using a new univariate and bivariate statistical model.
data_SC16 gives the computation time of SC16 algorithms.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Bantan, R. A., Shafiq, S., Tahir, M. H., Elhassanein, A., Jamal, F., Almutiry, W., & Elgarhy, M. (2022). Statistical Analysis of COVID-19 Data: Using A New Univariate and Bivariate Statistical Model. Journal of Function Spaces, 2022.
Biswas, A., & Chakraborty, S. (2021). A new method for constructing continuous distributions on the unit interval. arXiv preprint arXiv:2101.04661.
x<-data_SC16 summary(x)x<-data_SC16 summary(x)
The function allows to provide the service times of 63 aircraft windshields.
data_windshieldsdata_windshields
data_windshields |
A vector of (non-negative integer) values. |
The data refers to the service times of 63 aircraft windshields. Recently, it is used by Tahir et al. (2015) and fitted the Weibull-Lomax distribution.
data_windshields gives the service times of 63 aircraft windshields.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Tahir, M. H., Cordeiro, G. M., Mansoor, M., & Zubair, M. (2015). The Weibull-Lomax distribution: properties and applications. Hacettepe Journal of Mathematics and Statistics, 44(2), 455-474.
Ramos, M. W. A., Marinho, P. R. D., da Silva, R. V., & Cordeiro, G. M. (2013). The exponentiated Lomax Poisson distribution with an application to lifetime data. Advances and Applications in Statistics, 34(2), 107.
Murthy, D. P., Xie, M., & Jiang, R. (2004). Weibull models. John Wiley & Sons.
x<-data_windshields summary(x)x<-data_windshields summary(x)
The function allows to provide the 20 obervations representing the number of shocks before failure.
data_shocksdata_shocks
data_shocks |
A vector of (non-negative integer) values. |
An uncensored data of 20 obervations representing the number of shocks before failure. Recently, it is used by Cordeiro et al. (2016) and fitted an extended Birnbaum–Saunders distribution.
data_shocks gives the number of shocks before failure.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Cordeiro, G. M., Lima, M. D. C. S., Cysneiros, A. H., Pascoa, M. A., Pescim, R. R., & Ortega, E. M. (2016). An extended Birnbaum–Saunders distribution: Theory, estimation, and applications. Communications in Statistics-Theory and Methods, 45(8), 2268-2297.
Murthy, D.N.P., Xie, M., Jiang, R. (2004). Weibull Models. Hoboken, NJ: John Wiley.
data_breakdown, data_breakdownt, data_failureairc
x<-data_shocks summary(x)x<-data_shocks summary(x)
The function allows to provide the COVID-19 mortality rate in Somalia during the time between 1 st March 2021 to 20 th April 2021, with a total of 51 observed values.
data_RateMordata_RateMor
data_RateMor |
A vector of (non-negative integer) values. |
The data set contains the COVID-19 mortality rate from Somalia during the time between 1 st March 2021 to 20 th April 2021, with a total of 51 observed values. Recently, it is used by Muse et al. (2021) and fitted a new versatile modification of the log-logistic distribution.
data_RateMor gives the COVID-19 mortality rate from Somalia.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Muse, A. H., Tolba, A. H., Fayad, E., Abu Ali, O. A., Nagy, M., & Yusuf, M. (2021). Modelling the COVID-19 mortality rate with a new versatile modification of the log-logistic distribution. Computational Intelligence and Neuroscience, 2021.
data_COVIDDeath, data_COVID19MH, data_COVIDmor
x<-data_RateMor summary(x)x<-data_RateMor summary(x)
The function allows to provide the stream flow amounts (1000 acre-feet) for 35 year (1936–70) at the U.S. Geological Survey (USGS) gaging station number 9-3425 for April 1–August 31 of each year.
data_streamflowdata_streamflow
data_streamflow |
A vector of (non-negative integer) values. |
The data set consists of stream flow amounts (1000 acre-feet) for 35 year (1936–70) at the U.S. Geological Survey (USGS) gaging station number 9-3425 for April 1–August 31 of each year. Recently, it is used by Nawaz et al. (2020) and fitted the Kumaraswamy generalized Kappa distribution.
Stream Flow gives the stream flow amounts (1000 acre-feet) for 35 year (1936–70) at the U.S.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Nawaz, T., Hussain, S., Ahmad, T., Naz, F., & Abid, M. (2020). Kumaraswamy generalized Kappa distribution with application to stream flow data. Journal of King Saud University-Science, 32(1), 172-182.
MIELKE JR, P. W., & Johnson, E. S. (1973). Three-parameter kappa distribution maximum likelihood estimates and likelihood ratio tests. Monthly Weather Review, 101(9), 701-707.
x<-data_streamflow summary(x)x<-data_streamflow summary(x)
The function allows to provide the 63 observations which are generated to simulate the strengths of glass fibers.
data_glassfdata_glassf
data_glassf |
A vector of (non-negative integer) values. |
The data set consists of 63 observations which are generated to simulate the strengths of glass fibers. Recently, it is used by Afify et al. (2021) and fitted a new two-parameter burr-hatke distribution.
data_glassf gives the 63 observations which are generated to simulate the strengths of glass fibers.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Afify, A. Z., Aljohani, H. M., Alghamdi, A. S., Gemeay, A. M., & Sarg, A. M. (2021). A new two-parameter burr-hatke distribution: Properties and bayesian and non-bayesian inference with applications. Journal of Mathematics, 2021, 1-16.
Mahmoud, M. R., & Mandouh, R. M. (2013). On the transmuted Fréchet distribution. Journal of Applied Sciences Research, 9(10), 5553-5561.
x<-data_glassf summary(x)x<-data_glassf summary(x)
The function allows to provide the accelerated life testing of 40 items with a change in stress from 100 to 150 at t = 15.
data_Stressdata_Stress
data_Stress |
A vector of (non-negative integer) values. |
The data refers to accelerated life testing of 40 items with change in stress from 100 to 150 at t = 15. Recently, it is used by Cordeiro et al. (2016) and fitted an extended Birnbaum–Saunders distribution.
data_Stress gives the accelerated life testing of 40 items.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Cordeiro, G. M., Lima, M. D. C. S., Cysneiros, A. H., Pascoa, M. A., Pescim, R. R., & Ortega, E. M. (2016). An extended Birnbaum–Saunders distribution: Theory, estimation, and applications. Communications in Statistics-Theory and Methods, 45(8), 2268-2297.
Murthy, D.N.P., Xie, M., Jiang, R. (2004). Weibull Models. Hoboken, NJ: John Wiley.
data_breakdown, data_breakdownt, data_failureairc
x<-data_Stress summary(x)x<-data_Stress summary(x)
The function allows to provide the time intervals of the successive earthquakes. The dates of the successive earthquakes with magnitudes greater than or equal to 6 Mw (moment magnitude), which are recorded with their exact locations, magnitudes and depths between the years 1900 and 2000.
data_earthquakesdata_earthquakes
data_earthquakes |
A vector of (non-negative integer) values. |
The data set represents the time intervals of the successive earthquakes. The dates of the successive earthquakes with magnitudes greater than or equal to 6 Mw (moment magnitude), which are recorded with their exact locations, magnitudes and depths between the years 1900 and 2000. Recently, it is used by Kuş (2007) and fitted the the exponential–Poisson distribution.
data_earthquakes gives the time intervals of the successive earthquakes.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Kuş, C. (2007). A new lifetime distribution. Computational Statistics & Data Analysis, 51(9), 4497-4509.
x<-data_earthquakes summary(x)x<-data_earthquakes summary(x)
The function allows to provide the successive failures of air conditioning systems for the fleet of 13 Boeing 720 jet airplanes.
data_failureaircdata_failureairc
data_failureairc |
A vector of (non-negative integer) values. |
The data represent successive failures of air conditioning systems for a fleet of 13 Boeing 720 jet airplanes. Recently, the data set is used by Alsubie. A (2022) and fitted modified Kies–Lomax distribution with Estimation Methods.
data_failureairc gives the successive failure times of the air conditioning system.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alsubie, A. (2021). Properties and Applications of the Modified Kies–Lomax Distribution with Estimation Methods. Journal of Mathematics, 2021, 1-18.
Reyad, H., Korkmaz, M. Ç., Afify, A. Z., Hamedani, G. G., & Othman, S. (2021). The Fréchet Topp Leone-G family of distributions: Properties, characterizations and applications. Annals of Data Science, 8, 345-366.
Aldahlan, M. A., Afify, A. Z., & Ahmed, A. H. N. (2019). The odd inverse Pareto-G class: properties and applications. Journal of Nonlinear Sciences & Applications, 12(5), 278-290.
x<-data_failureairc summary(x)x<-data_failureairc summary(x)
The function allows to provide the 102 male and 100 female athletes collected at the Australian Institute of Sports, courtesy of Richard Telford and Ross Cunningham.
data_skinfoldsdata_skinfolds
data_skinfolds |
A vector of (non-negative integer) values. |
The data presents 102 male and 100 female athletes collected at the Australian Institute of Sports, courtesy of Richard Telford and Ross Cunningham. Recently, it is used by Tahir et al. (2021) and fitted the Kumaraswamy Pareto IV distribution.
data_skinfolds gives the 102 male and 100 female athletes collected at the Australian Institute of Sports.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Tahir, M. H., Cordeiro, G. M., Mansoor, M., Zubair, M., & Alzaatreh, A. (2021). The Kumaraswamy Pareto IV Distribution. Austrian Journal of Statistics, 50(5), 1-22.
Weisberg S (2005). Applied Linear Regression. Wiley, New York. ISBN 978-0-471-70409-6.
x<-data_skinfolds summary(x)x<-data_skinfolds summary(x)
The function allows to provide the survival time of animals observed due to different dosage of poison administered.
data_animalsdata_animals
data_animals |
A vector of (non-negative integer) values. |
The data represents the survival time of animals observed due to different dosage of poison administered. Recently, it is used by Kayal et al. (2017) and fitted the Burr XII distribution.
data_animals gives the survival time of animals.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Kayal, T., Tripathi, Y. M., Rastogi, M. K., & Asgharzadeh, A. (2017). Inference for Burr XII distribution under Type I progressive hybrid censoring. Communications in Statistics-Simulation and Computation, 46(9), 7447-7465.
data_relieftime, data_Bcancer, data_bloodcancer
x<-data_animals summary(x)x<-data_animals summary(x)
The function allows to provide the taxes revenue.
data_taxrevenuedata_taxrevenue
data_taxrevenue |
A vector of (non-negative integer) values. |
The data represents the taxes revenue. Recently, it is used by Ocloo et al. (2023) and fitted the extended Burr XII distribution.
data_taxrevenue gives the taxes revenue.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Ocloo, S. K., Brew, L., Nasiru, S., & Odoi, B. (2023). On the Extension of the Burr XII Distribution: Applications and Regression. Computational Journal of Mathematical and Statistical Sciences, 1-30.
Bhatti, F. A., Hamedani, G., Yousof, H. M., Ali, A., & Ahmad, M. (2018). On Modified Burr XII-Inverse Exponential Distribution: Prop¬ erties, Characterizations and Applications. Journal of Biostatistics & Biometrics.
x<-data_taxrevenue summary(x)x<-data_taxrevenue summary(x)
The function allows to provide the tensile strength for single carbon fibres (in GPa).
data_tstrengthdata_tstrength
data_tstrength |
A vector of (non-negative integer) values. |
The data set contains the tensile strength for single carbon fibers (in GPa). Recently, the data set is used by Alyami et al.(2022) and fitted the Topp–Leone modified Weibull model.
data_tstrength gives the tensile strength for single carbon fibers.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alyami, S. A., Elbatal, I., Alotaibi, N., Almetwally, E. M., Okasha, H. M., & Elgarhy, M. (2022). Topp–Leone Modified Weibull Model: Theory and Applications to Medical and Engineering Data. Applied Sciences, 12(20), 10431.
data_breakdown, data_breakdownt, data_failureairc
x<-data_tstrength summary(x)x<-data_tstrength summary(x)
The function allows to provide the times to each patient's third violation (V3) in ICU for varying periods.
data_ICUdata_ICU
data_ICU |
A vector of (non-negative integer) values. |
The data present the times of each patient's third violation (V3) in ICU for varying periods. Recently, it is used by Ijaz and Asim (2019) and fitted the odd Burr-III Lomax distribution.
data_ICU gives the times of each patient's third violation (V3) in ICU for varying periods.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Khan, M. S., King, R., & Hudson, I. L. (2017). Transmuted generalized exponential distribution: A generalization of the exponential distribution with applications to survival data. Communications in Statistics-Simulation and Computation, 46(6), 4377-4398.
Kang, I., Hudson, I., Rudge, A., & Chase, J. G. (2013). Density estimation and wavelet thresholding via Bayesian methods: A wavelet probability band and related metrics approach to assess agitation and sedation in ICU patients. Discrete Wavelet Transforms: A Compendium of New Approaches and Recent Applications. 1st ed. Rijeka: IntechOpen, 127-162.
x<-data_ICU summary(x)x<-data_ICU summary(x)
The function allows to provide the stress-rupture life of kevlar 49/epoxy strands that are subjected to constant sustained pressure at the 90 percent stress level until all have failed, so that the complete data set with the exact times of failure is recorded.
data_Kevlardata_Kevlar
data_Kevlar |
A vector of (non-negative integer) values. |
The data refer to in the 101 data points represent the stress-rupture life of kevlar 49/epoxy strands that are subjected to constant sustained pressure at the 90 percent stress level until all have failed, so that the complete data set with the exact times of failure is recorded. Recently, it is used by Oluyede et al. (2018) and fitted a new Burr XII-Weibull-logarithmic distribution.
data_Kevlar gives the stress-rupture life of kevlar 49/epoxy.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Oluyede, B. O., Makubate, B., Fagbamigbe, A. F., & Mdlongwa, P. (2018). A New Burr XII-Weibull-logarithmic distribution for survival and lifetime data analysis: model, theory and applications. Stats, 1(1), 77-91.
Cooray, K., & Ananda, M. M. (2008). A generalization of the half-normal distribution with applications to lifetime data. Communications in Statistics—Theory and Methods, 37(9), 1323-1337.
Andrews, D. F., & Herzberg, A. M. (2012). Data: a collection of problems from many fields for the student and research worker. Springer Science & Business Media.
Barlow, R. E., Toland, R. H., & Freeman, T. (1979). Stress-rupture life of kevlar/epoxy spherical pressure vessels (No. UCID-17755 (Pt.3)). California Univ., Livermore (USA). Lawrence Livermore Lab.
x<-data_Kevlar summary(x)x<-data_Kevlar summary(x)
The function allows to provide the prices of the 31 different children’s wooden toys on sale in a Suffolk craft shop in April 1991.
data_toyspricedata_toysprice
data_toysprice |
A vector of (non-negative integer) values. |
The data represents the prices of the 31 different children’s wooden toys on sale in a Suffolk craft shop in April 1991. Recently, it is used by Shafiei et al. (2016) and fitted the inverse Weibull power series distribution.
data_toysprice gives the prices of the 31 different children’s wooden toys on sale.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Shafiei, S., Darijani, S., & Saboori, H. (2016). Inverse Weibull power series distributions: properties and applications. Journal of statistical computation and simulation, 86(6), 1069-1094.
x<-data_toysprice summary(x)x<-data_toysprice summary(x)
The function allows to provide the mortality rate of COVID-19 patients in the United Kingdom (UK) from 1 December 2020 to 29 January 2021.
data_mortalityUKdata_mortalityUK
data_mortalityUK |
A vector of (non-negative integer) values. |
The data sets represent the mortality rate of COVID-19 patients in the UK from 1 December 2020 to 29 January 2021. Recently, it is used by Almetwally (2022) and fitted the odd Weibull inverse Lopp–Leone distribution.
data_mortalityUK gives the mortality rate of COVID-19 patients in the UK.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Almetwally, E. M. (2022). The odd Weibull inverse topp–leone distribution with applications to COVID-19 data. Annals of Data Science, 9(1), 121-140.
Nasiru, S., Abubakari, A. G., & Chesneau, C. (2022). New Lifetime Distribution for Modeling Data on the Unit Interval: Properties, Applications and Quantile Regression. Mathematical and Computational Applications, 27(6), 105.
data_COVIDDeath, data_COVIDfat, data_COVID19MH
x<-data_mortalityUK summary(x)x<-data_mortalityUK summary(x)
The function allows to provide the unemployment claims from July 2008 to April, reported by the Department of Labour, Licencing, and Regulation, USA.
data_insuranceundata_insuranceun
data_insuranceun |
A vector of (non-negative integer) values. |
The data set represents the unemployment claims from July 2008 to April, reported by the Department of Labour, Licencing, and Regulation, USA. Recently, it is used by Fayomi et al. (2022) and fitted a new useful exponential model.
data_insuranceun gives the unemployment claims from July 2008 to April.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Fayomi, A., Tahir, M. H., Algarni, A., Imran, M., & Jamal, F. (2022). A new useful exponential model with applications to quality control and actuarial data. Computational Intelligence and Neuroscience, 2022.
Afify, A. Z., Gemeay, A. M., & Ibrahim, N. A. (2020). The heavy-tailed exponential distribution: risk measures, estimation, and application to actuarial data. Mathematics, 8(8), 1276.
x<-data_insuranceun summary(x)x<-data_insuranceun summary(x)
The function allows to provide the complaints upheld against vehicle insurance firms as a proportion of their overall business over a two-year period. The study was conducted by DFR (Darla Fry Ross) insurance and investment company (2009–2016), registered in New York State.
data_vehicleinsurdata_vehicleinsur
data_vehicleinsur |
A vector of (non-negative integer) values. |
The data represent the complaints upheld against vehicle insurance firms as a proportion of their overall business over a two-year period. The study was conducted by DFR (Darla Fry Ross) insurance and investment company (2009–2016), registered in New York State. Recently, it is used by Khan et al. (2021) and fitted the An alternate generalized odd generalized exponential family with applications to premium data.
data_vehicleinsur gives the complaints upheld against vehicle insurance firms.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Khan, S., Balogun, O. S., Tahir, M. H., Almutiry, W., & Alahmadi, A. A. (2021). An alternate generalized odd generalized exponential family with applications to premium data. Symmetry, 13(11), 2064.
x<-data_vehicleinsur summary(x)x<-data_vehicleinsur summary(x)
The function allows to provide the vinyl chloride used for monitoring wells in mg/L.
data_vinyldata_vinyl
data_vinyl |
A vector of (non-negative integer) values. |
The data represent vinyl chloride used for monitoring wells in mg/L. Recently, it is used by Usman and Haq (2020) and fitted the Marshall-Olkin extended inverted Kumaraswamy distribution.
data_vinyl gives the vinyl chloride used for monitoring wells in mg/L.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Usman, R. M., & ul Haq, M. A. (2020). The Marshall-Olkin extended inverted Kumaraswamy distribution: Theory and applications. Journal of King Saud University-Science, 32(1), 356-365.
Bhaumik, D. K., Kapur, K., & Gibbons, R. D. (2009). Testing parameters of a gamma distribution for small samples. Technometrics, 51(3), 326-334.
x<-data_vinyl summary(x)x<-data_vinyl summary(x)
The function allows to provide the 100 observations about waiting times (in minutes) in a bank before the customers receive their services.
data_waitingtimedata_waitingtime
data_waitingtime |
A vector of (non-negative integer) values. |
The data contain 100 observations about waiting times (in minutes) in a bank before the customers receive their services. Recently, the data set is used by Alsubie. A (2022) and fitted modified Kies–Lomax distribution with estimation methods.
data_waitingtime gives the waiting times (in minutes) in a bank before the customers receive their services.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Alsubie, A. (2021). Properties and Applications of the Modified Kies–Lomax Distribution with Estimation Methods. Journal of Mathematics, 2021, 1-18.
Afify, A., Yousof, H., & Nadarajah, S. (2017). The beta transmuted-H family for lifetime data. Statistics and its Interface, 10(3), 505-520.
x<-data_waitingtime summary(x)x<-data_waitingtime summary(x)
The function allows to provide the waiting time of 100 bank customers.
data_bankdata_bank
data_bank |
A vector of (non-negative integer) values. |
The data set waiting time of 100 bank customers. Recently, it is used by Ijaz et al. (2020) and fitted a Gull alpha power Weibull distribution.
data_bank gives the waiting time of 100 bank customers.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Ijaz, M., Asim, S. M., Farooq, M., Khan, S. A., & Manzoor, S. (2020). A Gull Alpha Power Weibull distribution with applications to real and simulated data. Plos one, 15(6), e0233080.
Ghitany, M. E., Al-Awadhi, F. A., & Alkhalfan, L. (2007). Marshall–Olkin extended Lomax distribution and its application to censored data. Communications in Statistics—Theory and Methods, 36(10), 1855-1866.
x<-data_bank summary(x)x<-data_bank summary(x)
The function allows to provide the losses due to wind catastrophes recorded in 1977.
data_Lossesdata_Losses
data_Losses |
A vector of (non-negative integer) values. |
The data set represents the losses due to wind catastrophes recorded in 1977. Recently, it is used by Ijaz and Asim (2019) and fitted the odd Burr-III Lomax distribution.
data_Losses gives the losses due to wind catastrophes recorded in 1977.
Muhammad Imran.
R implementation and documentation: Muhammad Imran [email protected].
Ijaz, M., & Asim, S. M. (2019). Lomax exponential distribution with an application to real-life data. PloS one, 14(12), e0225827.
Ihtisham, S., Khalil, A., Manzoor, S., Khan, S. A., & Ali, A. (2019). Alpha-Power Pareto distribution: Its properties and applications. PloS one, 14(6), e0218027.
Hogg, R. V. (1984). S. A. Klugman, Loss Distributions. New York Wiley, 569-574.
x<-data_Losses summary(x)x<-data_Losses summary(x)