Generalizing distributions is an old practice and has ever been considered as precious as
many other practical problems in statistics. It simply started with defining different …

The subject of this book is cross-disciplinary. Sigmoid functions present interesting material
both for fundamental as well as application-driven research. We have tried to give the …

This paper aims to find a statistical model for the COVID-19 spread in the United Kingdom
and Canada. We used an efficient and superior model for fitting the COVID 19 mortality rates …

Transmutation is the functional composition of the cumulative distribution function (cdf) of
one distribution with the inverse cumulative distribution function (quantile function) of …

This article introduces a two-parameter probability model which represents another
generalization of the Inverse Exponential distribution by using the quadratic rank transmuted …

In this article, the so called Transmuted Exponential (TE) distribution was applied to two real
life datasets to assess its potential flexibility over some other generalized models. Various …

Big data is a collection of complex and large volumes of data that is not easily handled by
the traditional process. The top ten big data science communities include Kaggle, IBM data …

This paper introduces a new four-parameter lifetime model, which extends the Marshall-
Olkin Fréchet distribution introduced by Krishna et al.(2013), called the transmuted Marshall …

In this research article, we formulate a new lifetime probability model, named Power
Rayleigh distribution (PRD). Numerous significant properties of PRD are acquired including …

The main goal of the current paper is to contribute to the existing literature of probability
distributions. In this paper, a new probability distribution is generated by using the Alpha …