Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/29931
Title: Some perspectives on the problem of model selection
Authors: TRAN MINH NGOC
Keywords: lasso, loss rank, model complexity, model selection, variable selection, variational Bayes
Issue Date: 6-Jun-2011
Source: TRAN MINH NGOC (2011-06-06). Some perspectives on the problem of model selection. ScholarBank@NUS Repository.
Abstract: Model selection in general and variable selection in particular are fundamental problems in statistics. This thesis makes some contributions to the literature by introducing two general procedures for model selection. The first procedure can be considered as a guiding principle for designing model selection criteria that help avoid overfitting, while the second aims at selecting good models in terms of predictive performance. The thesis also introduces two novel algorithms for variable selection in very general frameworks including generalized linear models, heteroscedastic linear regression and regression with mixtures of heteroscedastic experts.
URI: http://scholarbank.nus.edu.sg/handle/10635/29931
Appears in Collections:Ph.D Theses (Open)

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