文章基本信息
- 标题：A New Flexible Probability Model: Theory, Estimation and Modeling Bimodal Left Skewed Data
- 本地全文：下载
- 作者：Mohamed Aboraya ; M.Masoom Ali ; Haitham M.Yousof 等
- 期刊名称：Pakistan Journal of Statistics and Operation Research
- 印刷版ISSN：2220-5810
- 出版年度：2022
- 卷号：18
- 期号：2
- 页码：437-463
- DOI：10.18187/pjsor.v18i2.3938
- 语种：English
- 出版社：College of Statistical and Actuarial Sciences
- 摘要：In this work, we introduced a new three-parameter Nadarajah-Haghighi model. We derived explicit expressions for some of it statistical properties. The Farlie Gumbel Morgenstern, modified Farlie Gumbel Morgenstern, Clayton, Renyi and Ali-Mikhail-Haq copulas are used for deriving some bivariate type extensions. We consider maximum likelihood, Cramér-von-Mises, ordinary least squares, whighted least squares, Anderson Darling, right tail Anderson Darling and left tail Anderson Darling estimation procedures to estimate the unknown model parameters. Simulation study for comparing estimation methods is performed. An application for comparing methods as also presented. The maximum likelihood estimation method is the best method. However, the other methods performed well. Another application for comparing the competitive models is investigated.
- 关键词：Nadarajah Haghighi model;
Farlie Gumbel Morgenstern;
Anderson Darling;
Maximum Likelihood Estimation;
Ordinary Least Squares;
Generating Function;
Moments
