Journal of the Korean Data and Information Science Society
- Volume 9 Issue 2
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- Pages.165-172
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- 1998
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- 1598-9402(pISSN)
Bayesian Estimation for the Multiple Regression with Censored Data : Mutivariate Normal Error Terms
Abstract
This paper considers a linear regression model with censored data where each error term follows a multivariate normal distribution. In this paper we consider the diffuse prior distribution for parameters of the linear regression model. With censored data we derive the full conditional densities for parameters of a multiple regression model in order to obtain the marginal posterior densities of the relevant parameters through the Gibbs Sampler, which was proposed by Geman and Geman(1984) and utilized by Gelfand and Smith(1990) with statistical viewpoint.
Keywords
- Multiple Regression;
- Multivariate Normal Error Terms;
- Censored Data;
- Bayesian Estimation;
- Gibbs Sampler