Bayes estimators in linear regression model
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Abstract (EN)
To remedy the problem of multicollinearity some biased estimators are proposed is an alternative to the ordinary least squares (OLS) estimator. One of these estimators is Bayes estimator. In this study, the main structures and methods to carry out the Bayesian analysis are indicated. Also, Bayesian estimation methods in linear regression model are investigated. Subsequently, Liu and ridge type estimators are examined by carrying the Bayesian approach to the distributed lag models. Two new Liu-type Bayesian estimators are obtained by using Shiller and Lindley estimator, which are belong to Ridge-type Bayesian estimators, with Liu-type Bayesian introduced by Gruber (2012).
Author
Nimet Türker
Institution
How to Cite
Nimet Türker (Master Thesis). Bayes estimators in linear regression model, 2013, Çukurova University.
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