Use of Mixture of Distributions for the Error in Regression Models for Lifetime Data
نویسندگان
چکیده
In this paper we present a Bayesian analysis of location-scale regression models assuming standard lifetime distributions and an additional error term with a mixture of normal distributions. Considering a censored lifetime data set, we use Gibbs sampling with Metropolis-Hastings algorithm to get Bayesian quantities of interest. The proposed regression model gives a great flexibility to fit lifetime data as we see in an example.
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