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A novel Bayesian approach for latent variable modeling from mixed data with missing values
We consider the problem of learning parameters of latent variable models from mixed (continuous and ordinal) data with missing values. We propose a novel Bayesian Gaussian copula factor (BGCF) approach that is proven to be consistent when the data are missing completely at random (MCAR) and that is empirically quite …