Estimation in the Birnbaum-Saunders distribution based on scale-mixture of normals and the EM-algorithm

被引：0

作者：

Balakrishnan, N. ^{[2
]}

Leiva, Victor ^{[1
]}

Sanhueza, Antonio ^{[3
]}

Vilca, Filidor ^{[4
]}

机构：

[1] Univ Valparaiso, CIMFAV, Dept Stat, Valparaiso, Chile

[2] McMaster Univ, Dept Math & Stat, Hamilton, ON, Canada

[3] Univ La Frontera, Dept Math & Stat, Temuco, Chile

[4] Univ Estadual Campinas, Dept Stat, Sao Paulo, Brazil

来源：

SORT-STATISTICS AND OPERATIONS RESEARCH TRANSACTIONS | 2009年 / 33卷 / 02期

基金：

巴西圣保罗研究基金会;

关键词：

Birnbaum-Saunders distribution; EM-algorithm; kurtosis; maximum likelihood methods; robust estimation; scale mixtures of normal distributions; REGRESSION-MODELS; INFLUENCE DIAGNOSTICS; ROBUSTNESS; LOCATION; FAMILY;

D O I：

暂无

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

Scale mixtures of normal (SMN) distributions are used for modeling symmetric data. Members of this family have appealing properties such as robust estimates, easy number generation, and efficient computation of the ML estimates via the EM-algorithm. The Birnbaum-Saunders (BS) distribution is a positively skewed model that is related to the normal distribution and has received considerable attention. We introduce a type of BS distributions based on SMN models, produce a lifetime analysis, develop the EM-algorithm for ML estimation of parameters, and illustrate the obtained results with real data showing the robustness of the estimation procedure.

引用

页码：171 / 191

页数：21

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