An EM Estimation Approach for Analyzing Bivariate Skew Normal Data with Non monotone Missing Values

被引：11

作者：

Baghfalaki, T. ^{[1
]}

Ganjali, M. ^{[1
]}

机构：

[1] Shahid Beheshti Univ, Dept Stat, Tehran, Iran

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2011年 / 40卷 / 09期

关键词：

Bootstrap; EM algorithm; Non monotone missingness; Skew normal distribution; PATTERN-MIXTURE MODELS; INCOMPLETE DATA; REGRESSION-MODELS; DISTRIBUTIONS; ALGORITHM; LIKELIHOOD; INFERENCE;

D O I：

10.1080/03610921003637454

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：

In this article, an EM algorithm approach to obtain the maximum likelihood estimates of parameters for analyzing bivariate skew normal data with non monotone missing values is presented. A simulation study is implemented to investigate the performance of the presented algorithm. Results of an application are also reported where a Bootstrap approach is used to find the variances of the parameter estimates.

引用

页码：1671 / 1686

页数：16

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