Bayesian Variants of Some Classical Semiparametric Regression Techniques.

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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Year of publication:	2000
Authors:	Koop, G. ; Poirier, D.
Institutions:	California Irvine - School of Social Sciences
Subject:	MODELS \| TESTS \| MATHEMATICAL ANALYSIS

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Series:	California Irvine - School of Social Sciences.
Type of publication:	Book / Working Paper
Notes:	30 pages
Classification:	C14 - Semiparametric and Nonparametric Methods ; C11 - Bayesian Analysis
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005671615