The polar-generalized normal distribution: properties, Bayesian estimation and applications

被引：3
|
作者：
Faridi, Masoud [1 ]
Khaledi, Majid Jafari [1 ]
机构：
[1] Tarbiat Modares Univ, Dept Stat, Tehran, Iran
来源：
STATISTICAL PAPERS | 2022年 / 63卷 / 02期
关键词：
Skewness; Bimodality; Polar method; Beta distribution; Bayesian estimation; GENE-EXPRESSION; BIMODALITY; EXTENSION;
D O I：
10.1007/s00362-021-01245-0
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
This paper introduces an extension to the normal distribution through the polar method to capture bimodality and asymmetry, which are often observed characteristics of empirical data. The later two features are entirely controlled by a separate scalar parameter. Explicit expressions for the cumulative distribution function, the density function and the moments were derived. The stochastic representation of the distribution facilitates implementing Bayesian estimation via the Markov chain Monte Carlo methods. Some real-life data as well as simulated data are analyzed to illustrate the flexibility of the distribution for modeling asymmetric bimodality.
引用
收藏
页码：571 / 603
页数：33
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