Package: ComRiskModel
Type: Package
Title: Fitting of Complementary Risk Models
Version: 0.2.0
Date: 2023-05-14
Authors@R: c(
           person( "Muhammad", "Imran", role = c("aut", "cre"), email = "imranshakoor84@yahoo.com" ),
           person("M.H", "Tahir", role = "aut", email = "mht@iub.edu.pk"))
Author: Muhammad Imran [aut, cre], M.H Tahir [aut]
Maintainer: Muhammad Imran <imranshakoor84@yahoo.com>
Depends: R (>= 2.0)
Imports: AdequacyModel, graphics, stats
Description: Evaluates the probability density function (PDF),
        cumulative distribution function (CDF), quantile function (QF),
        random numbers and maximum likelihood estimates (MLEs) of
        well-known complementary binomial-G, complementary negative
        binomial-G and complementary geometric-G families of
        distributions taking baseline models such as exponential,
        extended exponential, Weibull, extended Weibull, Fisk, Lomax,
        Burr-XII and Burr-X. The functions also allow computing the
        goodness-of-fit measures namely the
        Akaike-information-criterion (AIC), the
        Bayesian-information-criterion (BIC), the minimum value of the
        negative log-likelihood (-2L) function, Anderson-Darling (A)
        test, Cramer-Von-Mises (W) test, Kolmogorov-Smirnov test,
        P-value and convergence status. Moreover, some commonly used
        data sets from the fields of actuarial, reliability, and
        medical science are also provided. Related works include: a)
        Tahir, M. H., & Cordeiro, G. M. (2016). Compounding of
        distributions: a survey and new generalized classes. Journal of
        Statistical Distributions and Applications, 3, 1-35.
        <doi:10.1186/s40488-016-0052-1>.
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 7.2.3
NeedsCompilation: no
Packaged: 2026-10-09 07:52:33 UTC; root
Repository: https://imranshakoor.r-universe.dev
Date/Publication: 2023-05-15 06:36:04 UTC
RemoteUrl: https://github.com/cran/ComRiskModel
RemoteRef: HEAD
RemoteSha: d0b795e97fba7674beb3f6a421a457d226b99f9f