Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/9853
Title: Comparing distributions by using dependent normalized random-measure mixtures
Authors: Griffin, Jim E. 
Kolossiatis, Michalis 
Steel, Mark F J 
Keywords: Bayesian non-parametrics
Dependent distributions
Dirichlet process
Normalized generalized gamma process
Slice sampling
Utility function
Issue Date: 1-Jun-2013
Publisher: Wiley-Blackwell
Source: Journal of the Royal Statistical Society, Series B: Statistical Methodology, 2013, Volume 75, Issue 3, Pages 499-529
Abstract: A methodology for the simultaneous Bayesian non-parametric modelling of several distributions is developed. Our approach uses normalized random measures with independent increments and builds dependence through the superposition of shared processes. The properties of the prior are described and the modelling possibilities of this framework are explored in detail. Efficient slice sampling methods are developed for inference. Various posterior summaries are introduced which allow better understanding of the differences between distributions. The methods are illustrated on simulated data and examples from survival analysis and stochastic frontier analysis.
URI: http://ktisis.cut.ac.cy/handle/10488/9853
ISSN: 13697412
Rights: © 2013 Royal Statistical Society.
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