Bayer FM, Cribari-Neto F (2017) Model selection criteria in beta regression with varying dispersion. Com- munications in Statistics - Simulation and Computation 46(1):729-746Bayer, F.M.; Cribari-Neto, F. Model selection criteria in beta regression with varying dispersion. Commun. Stat. Simul...
2. Can different optimalities be attained simultaneously by a powerful learning procedure? In this talk, I will give a glimpse of some foundational theories on model selection for optimal regression learning. First, we will under...
This paper discusses the problem of choosing a linear model from a set of nested alternatives. Two popular devices for selecting a model in this situation have been model selection criteria and conditional test sequences (model selection tests). If there are only two alternative models then choosi...
Abstract The following sections are included: Model Description Model Structure and Notation Distance Measures Derivations of the Foundation Model Selection Criteria Moments of Model Selection Crit...
Criteria for Linear Model Selection Based on Kullback's Symmetric Divergence SummaryModel selection criteria are frequently developed by constructing estimators of discrepancy measures that assess the disparity between the 'true' mo... Joseph,E.,Cavanaugh - 《Australian & New Zealand Journal of Statistic...
Prediction, model selection, and causal inference with regularized regression Introducing two Stata packages: LASSOPACK and PDSLASSO Achim Ahrens (ESRI, Dublin), Mark E Schaffer (Heriot-Watt University, CEPR & IZA), with Christian B Hansen (University of Chicago) https://statalasso.github.io/ ...
probability closest to 0 or 1 can be seen as the high confidence sample. It is easy to find that the difference between the self-training and uncertainty sampling is that the selection criteria of identifying the used unlabeled samples. Hence the self-training logistic regression model is shown...
In this paper, we study integrated regression techniques to check the adequacy of a given model in the context of selection-biased observations. We introduce integrated regression in this setting, providing not only a suitable statistic for enabling a model checking test, but also a bootstrap dist...
The performance of six existing model selection criteria is compared, which are commonly used in time series and regression analysis, when they are applied... P Chen,TJ Wu,J Yang - 《Iet Radar Sonar & Navigation》 被引量: 62发表: 2008年 Model Uncertainty and Health Effect Studies for Parti...
lassopack: Model selection and prediction with regularized regression in Statalasso2cvlassorlassolassoelastic netsquare-root lassocross-validationThis article introduces lassopack, a suite of programs for regularized regression in Stata. lassopack implements lasso, square-root lasso, elastic net, ridge ...