Total Quality Science
Online ISSN : 2189-3195
ISSN-L : 2189-3195
Comparison of model selection methods for the estimation of principal points for a multivariate binary distribution
Haruka YamashitaShun MatsuuraHideo Suzuki
Author information
JOURNALS FREE ACCESS

2015 Volume 1 Issue 1 Pages 22-31

Details
Abstract

Recently, a parametric estimation method for principal points for a multivariate binary distribution using a log-linear model has been proposed, and Akaike information criterion (AIC) has been applied to model selection for log-linear model. This paper compares three model selection methods based on AIC, Bayesian information criterion (BIC), and the likelihood ratio test (LRT) for estimating principal points for a multivariate binary distribution. The performances of the model selection methods are shown through numerical simulation studies

Information related to the author
© 2015 The Japanese Society for Quality Control
Previous article Next article
feedback
Top