%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