Over the course of the last several decades, many algebraic generalised families and classes of s... more Over the course of the last several decades, many algebraic generalised families and classes of statistical distributions have been developed. The purpose of this research is to construct a brand new cotangent exponentiated generalized and generator of distributions that have support on the real line. After that, two novel families of distributions incorporating the cotangent function are proposed: one called the cotangent exponentiated generalised (CE-G) family, and the other called the logistic cotangent exponentiated generalised (LCE-G) family. A comprehensive analysis of the mathematical and structural properties of the recently suggested G-family as well as a Burr-based novel model (LCEB) is presented here. The maximum likelihood approach is used in Monte-Carlo simulation studies to estimate model parameters and evaluate performance. This is done using the maximum likelihood method. The statistical analysis on the survival and waiting times data sets is carried out, and the outcomes confirm the competence, superiority, and utility of the suggested generator, G-family, and novel distribution in comparison to similar and competing Burr-based models that are already well-known.
Over the course of the last several decades, many algebraic generalised families and classes of s... more Over the course of the last several decades, many algebraic generalised families and classes of statistical distributions have been developed. The purpose of this research is to construct a brand new cotangent exponentiated generalized and generator of distributions that have support on the real line. After that, two novel families of distributions incorporating the cotangent function are proposed: one called the cotangent exponentiated generalised (CE-G) family, and the other called the logistic cotangent exponentiated generalised (LCE-G) family. A comprehensive analysis of the mathematical and structural properties of the recently suggested G-family as well as a Burr-based novel model (LCEB) is presented here. The maximum likelihood approach is used in Monte-Carlo simulation studies to estimate model parameters and evaluate performance. This is done using the maximum likelihood method. The statistical analysis on the survival and waiting times data sets is carried out, and the outcomes confirm the competence, superiority, and utility of the suggested generator, G-family, and novel distribution in comparison to similar and competing Burr-based models that are already well-known.
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Papers by Muhammad Akbar