Abstract

We propose and study a new compounded model to extend the half-Cauchy and power-Cauchy distributions, which offers more flexibility in modeling lifetime data. The proposed model is analytically tractable and can be used effectively to analyze censored and uncensored data sets. Its density function can have various shapes such as reversed-J and right-skewed. It can accommodate different hazard shapes such as decreasing, upside-down bathtub and decreasing-increasing-decreasing. Some mathematical properties of the new distribution can be determined from a linear combination for its density function such as ordinary and incomplete moments. The performance of the maximum likelihood method to estimate the model parameters is investigated by a simulation study. Further, we introduce the new log-power-Cauchy negative-binomial regression model for censored data, which includes as sub-models some widely known regression models that can be applied to censored data. Four real life data sets, of which one is censored, have been analyzed and the new models provide adequate fits.

Highlights

  • Numerous extended classical distributions have been proposed for modelling data in several areas such as biological studies, environmental and medical sciences, engineering, economics, finance and actuarial science

  • In “Regression model” section, we present a regression model based on the power-Cauchy negative-binomial (PCNB) distribution with censored data

  • Properties of the new model we provide some structural properties of the new distribution

Read more

Summary

Introduction

Numerous extended classical distributions have been proposed for modelling data in several areas such as biological studies, environmental and medical sciences, engineering, economics, finance and actuarial science. In many applied areas like lifetime analysis, finance and insurance, there is a clear need for further extended distributions, that is, new distributions which are more flexible to model real data in these areas, since the data can present a high degree of skewness and kurtosis. There are many generalizations and extensions of distributions in literature using the randomly-stopped approach for either the minimum or maximum of K independent and identically distributed (iid) random variables (discrete or continuous). Rooks et al (2010) introduced a two-parameter power-Cauchy (PC) distribution for analyzing upside-down bathtub (UBT) hazard function data. The cumulative distribution function (cdf ) and probability density function (pdf ) of the PC distribution with shape parameter α and scale parameter σ are, respectively, given by Zubair et al Journal of Statistical Distributions and Applications (2018) 5:1

Objectives
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call