Mixtures density estimation in lifetime data analysis: an application of nonparametric Bayesian estimation technique.
Hossain, Ahmed and Khan, Hafiz T. A. (2010) Mixtures density estimation in lifetime data analysis: an application of nonparametric Bayesian estimation technique. Journal of Statistics & Management Systems, 13 (3). pp. 605-615. ISSN 0972-0510
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In this paper we review a nonparametric Bayesian estimation technique in mixture of
distributions employing a flexible Dirichlet process mixture. Methods for simulation based
model fitting, in the presence of censoring, and for prior specification are provided. Using the method it allows dealing with a variety of practical issues including estimating density
function, survival function, hazard function etc. Our interest on the other hand is to identify
the underlying components of mixtures in a dataset by mixture model analysis. We thus
illustrate our model with a simulated and a real data set under Type I censoring considering
mixture of Weibull distributions. These illustrations demonstrate that modeling data in an
infinite mixture works well when there are only a small finite number of components in the
|Research Areas:||A. > School of Law > Criminology and Sociology|
|Depositing User:||Ms Jyoti Zade|
|Date Deposited:||03 Feb 2011 11:04|
|Last Modified:||18 Mar 2015 11:54|
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