BAYESIAN PROCRUSTES SOLUTION

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概要

• 論文の詳細を見る

• A new Bayesian method was proposed to obtain the optimal solution when the prior knowledge was given as a target factor pattern matrix. This method (Bayesian Procrustes Solution ) chooses the best target matrix in terms of the posterior probability or Bayes factor when there are two or more possible target matrices. Then the posterior distributions of the relevant parameters are approximated by a sufficient large sample of parameters simulated by the Gibbs sampler. The estimates of the parameters are given as the means of these distributions. The simulation study demonstrated that this method has more robustness with respect to misspecification of the target matrix than the traditional method. Finally, the application of this method to the real data showed the validity of this method.

• 日本行動計量学会の論文

著者

• Shigemasu Kazuo

  Department Of Cognitive And Behavioral Science The University Of Tokyo

• Hoshino Takahiro

  Department Of Cognitive And Behavioral Science The University Of Tokyo

関連論文

• BAYESIAN PROCRUSTES SOLUTION
• BAYESIAN INFERENCE FOR FINITE MIXTURES IN CONFIRMATORY FACTOR ANALYSIS
• A LATENT VARIABLE MODEL WITH NON-IGNORABLE MISSING DATA
• A BAYESIAN HIERARCHICAL LINEAR MODEL WITH EDUCATIONAL APPLICATIONS
• A BAYESIAN MARGINAL INFERENCE IN ESTIMATING ITEM PARAMETERS USING THE GIBBS SAMPLER

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