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Comparison of model selection methods for the estimation of principal points for a multivariate binary distribution
2015
Total Quality Science
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
doi:10.17929/tqs.1.22
fatcat:mmdq6y75ezbupo4onzuxe4xu7m