- Proposes new univariate continuous and discrete G families of probability distributions.
- Discusses new bivariate continuous and discrete G families of probability distributions.
- Reviews useful mathematical properties such as, ordinary and incomplete moments, moments generating functions, residual life and reversed residual life functions, order statistics, quantile spread ordering and entropies, among others and some bivariate and multivariate extensions of the new and existing models using a simple type copula.
- Assess the performance of the used estimation methods via Monte-Carlo simulation studies.
- Shows the wide importance and the flexibility of the new models against the competitive models.
- Constructs some new regression models based on the new proposed G families and use in statistical prediction.
- Shows the application of many new useful goodness-of-fit tests for right censored validation such as the Nikulin-Rao-Robson goodness-of-fit test, modified Nikulin-Rao-Robson goodness-of-fit test, Bagdonavicius-Nikulin goodness-of-fit test and modified Bagdonavicius-Nikulin goodness-of-fit test to the new families.
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