ComRiskModel: Fitting of Complementary Risk Models

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>.

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