This paper develops new Bayesian methods for semiparametric inference in the partial linear Normal regression model. These methodes draw solely on teh Normal linear regression model with natural conjugate prior. Hence, analytical finite sample results are available which do not suffer form problems of theoretical and computational complexity which plague the existing literature.
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Paper provided by California Irvine - School of Social Sciences in its series Papers with number
00-01-22.
Find related papers by JEL classification: C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
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