GIBBS SAMPLING APPROACH TO VARIABLE SELECTION IN LINEAR REGRESSION WITH OUTLIER VALUES

被引：0

作者：

Yardimci, Atilla ^{[1
]}

Erar, Aydin ^{[2
]}

机构：

[1] Turkiye Odalar & Borsalar Birligi, Bilgi Hizmetleri Dairesi, TR-06640 Ankara, Turkey

[2] Mimar Sinan Univ, Fen Edebiyat Fak, Istat Bolumu, TR-34349 Istanbul, Turkey

来源：

GAZI UNIVERSITY JOURNAL OF SCIENCE | 2005年 / 18卷 / 04期

关键词：

Bayesian variable selection; prior distribution; Gibbs sampling; Markov Chain Monte Carlo; outlier values; entropy;

D O I：

暂无

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

In this study, Gibbs sampling has been applied to the variable selection in the linear regression model with outlier values. Gibbs sampling has been compared with classical variable selection criteria by using dummy data with different beta and priors.

引用

页码：603 / 611

页数：9

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