%0 Electronic Article
%A Quintana, Fernando A. and Müller, Peter and Papoila, Ana Luisa
%I Wiley
%D 2015
%D 2015
%G English
%@ 0303-6898
%@ 1467-9469
%~ Katalog der Universitätsbibliothek Leipzig
%T Cluster‐Specific Variable Selection for Product Partition Models
%V 42
%J Scandinavian Journal of Statistics
%V 42
%N 4
%P 1065-1077
%U http://dx.doi.org/10.1111/sjos.12151
%X AbstractWe propose a random partition model that implements prediction with many candidate covariates and interactions. The model is based on a modified product partition model that includes a regression on covariates by favouring homogeneous clusters in terms of these covariates. Additionally, the model allows for a cluster‐specific choice of the covariates that are included in this evaluation of homogeneity. The variable selection is implemented by introducing a set of cluster‐specific latent indicators that include or exclude covariates. The proposed model is motivated by an application to predicting mortality in an intensive care unit in Lisboa, Portugal.
%Z https://katalog.ub.uni-leipzig.de/Record/ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTExMS9zam9zLjEyMTUx
%U https://katalog.ub.uni-leipzig.de/Record/ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTExMS9zam9zLjEyMTUx