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
收藏
页码：1671 / 1686
页数：16
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