Estimation of Inverse Pareto Distribution through Different Loss Functions on Mortality Rate of COVID Data

Authors

  • Dr. Zaki Anwar
  • Iftkhar Khan
  • Dr. Mohammad Azam Khan
  • Zakir Ali

Keywords:

Inverse Pareto distribution, Record values, Maximum Likelihood Estimates (MLE), SELF, LINEX, GELF, Bayesian estimation, Covid data.

Abstract

In this paper, the main objective is to estimate the parameter of inverse Pareto distribution based on lower record values. Hence, we consider the classical and Bayesian approaches to estimate the parameters of Inverse Pareto distribution (IPD), such as Maximum likelihood estimator(MLE), the general entropy loss function (GELF), the square error loss function (SELF), and the linear exponential loss function (LINEX). Further, simulation studies are performed to compare the different loss functions and confidence interval is also obtained for the given parameter. At last, covid data are used to compare the different results of estimations.

Keywords: Inverse Pareto distribution, Record values, Maximum Likelihood Estimates (MLE), SELF, LINEX, GELF, Bayesian estimation, Covid data.

2010 Mathematics Subject Classification. 62F10 ; 62F15

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Published

2025-10-13

How to Cite

Dr. Zaki Anwar, Iftkhar Khan, Dr. Mohammad Azam Khan, & Zakir Ali. (2025). Estimation of Inverse Pareto Distribution through Different Loss Functions on Mortality Rate of COVID Data. Jordan Journal of Mathematics and Statistics, 18(3), 369–379. Retrieved from https://jjms.yu.edu.jo/index.php/jjms/article/view/1416

Issue

Vol. 18 No. 3 (2025)

Section

Articles