On the Finite Mixture Modeling via Normal Mean-Variance Birnbaum-Saunders Distribution

Authors

10.18869/acadpub.jirss.16.1.1003

Abstract

This paper presents a new finite mixture model using the normal mean-variance mixture of Birnbaum-Saunders distribution. The proposed model is multi-modal with wider ranges of skewness and kurtosis. Moreover, it is useful for modeling highly asymmetric data in various theoretical and applied statistical problems. The maximum likelihood estimates of the parameters of the model are computed iteratively by feasible EM algorithm. To illustrate the finite sample properties and performance of the estimators, we conduct a simulation study and illustrate the usefulness of the new model by analyzing a real dataset.

Keywords

Volume 16, Issue 1
June 2017
Pages 33-51
  • Receive Date: 23 July 2022
  • Revise Date: 19 May 2024
  • Accept Date: 23 July 2022