Pervasive application of data mining technology is very important in analytical CRM software development when the distributed data warehouse is constructed. We propose a multi-factor customer classification evaluation model CLV/CL/CC which comprehensively considers customer lifetime value, customer loyalty and customer credit. It classifies clients with synthetic data mining algorithms. In this...

The main purpose of this article is to develop a Bayesian approach for a general multigroup nonlinear factor analysis model. Joint Bayesian estimates of the factor scores and the structural parameters subjected to some constraints across different groups are obtained simultaneously. A hybrid algorithm that combines the Metropolis-Hastings algorithm and the Gibbs sampler is implemented to produc...

Corrigendum to “Bayesian model selection for group studies” [NeuroImage 46 (2009) 1005–1017] Klaas Enno Stephan ⁎, Will D. Penny , Jean Daunizeau , Rosalyn J. Moran , Karl J. Friston a a Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3BG, UK b Laboratory for Social and Neural Systems Research, Institute for Empirical Rese...

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In this work we approach the problem of model comparison between skew families. For the univariate skew model, we measure the sensitivity of the skewness parameter using the L1-distance between symmetric and asymmetric models and we obtain explicit expressions for some of these models. The main result is that the L1-distance between a representable elliptical distribution and a representable sk...

I review the observational prospects to constrain the equation of state parameter of dark energy and I discuss the potential of future imaging and redshift surveys. Bayesian model selection is used to address the question of the level of accuracy on the equation of state parameter that is required before explanations alternative to a cosmological constant become very implausible. I discuss resu...

Daryl J. Bem. Cornell University Jessica Utts and Wesley O. Johnson University of California, Irvine We agree with Wagenmakers, Wetzels, Borsboom, & van der Maas (2011) that there are advantages to analyzing data with Bayesian statistical procedures, but we argue that they have incorrectly characterized several features of Bem’s (2011) psi experiments and have selected an unrealistic Bayesian p...

It has long been known that for the comparison of pairwise nested models, a decision based on the Bayes factor produces a consistent model selector (in the frequentist sense). Here we go beyond the ∗Distinguished Professor, Department of Statistics, University of Florida, Gainesville, FL 32611. Supported by National Science Foundation Grant DMS-04-05543. Email: [email protected]. †Professor,...

A predictive Bayesian model selection approach is presented to discriminate coupled models used to predict an unobserved quantity of interest (QoI). The need for accurate predictions arises in a variety of critical applications such as climate, aerospace and defense. A model problem is introduced to study the prediction yielded by the coupling of two physics/subcomponents. For each single physi...