Parameter estimation for power function-lognormal composite distribution

Abstract

In this paper, a new kind of composite model, the power function–lognormal composite (PFLC), is proposed. Four estimators of the new distribution are discussed. These are maximum likelihood, moment, nonlinear least squares, and Bayes estimators. A simulation study is performed, and numerical computations are carried out to demonstrate the performance of the proposed methods. Finally, datasets concerning annual income and insurance claims data are analyzed for illustrative purposes.

Keywords:

• Power function-lognormal composite (PFLC) distribution
• composite models
• parameter estimation
• income data
• insurance claim data

Additional information

Funding

The author gratefully acknowledges the editor and two anonymous referees for their insightful comments and constructive suggestions that led to a marked improvement of the article. This paper was partially supported by the National Social Science Fund of China (Grant No. 19BTJ051), and General project of Humanities and Social Sciences of the Education Department of Henan Province (Grant No. 2020-ZZJH-044).