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A Sequence of Relaxations Constraining Hidden Variable Models
Sequence Relaxations Constraining Hidden Variable Models
2011/7/6
Many widely studied graphical models with latent variables lead to nontrivial constraints on the distribution of the observed variables. Inspired by the Bell inequalities in quantum mechanics, we refe...
Estimation of latent variable models for ordinal data via fully exponential Laplace approximation
GLLVM Bartholomew response pattern parameters latent variable models Laplace
2011/6/17
Latent variable models represent a useful tool in the social sciences where the analyzed
constructs cannot be directly observed and, hence, they are not measurable. However, a set
of indicators rela...
Semiparametric Latent Variable Models for Guided Representation
Variable Models Semiparametric Latent Guided
2011/3/18
Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for learning features re...
Bayesian auxiliary variable models for binary and multinomial regression
Auxiliary variables Bayesianb inary and multinomial regression Model averaging Scale mixture of normals
2009/9/21
In this paper we discuss auxiliary variable approaches to Bayesia
binary and multinomial regression. These approaches are ideally suited to au
tomated Markov chain Monte Carlo simulation. In the rst...
DE-BIASING WEIGHTED MLE VIA INDIRECT INFERENCE:THE CASE OF GENERALIZED LINEAR LATENT VARIABLE MODELS
factor analysis latent variables M-estimators
2009/2/25
In this paper we study bias-corrections to the weighted MLE (Dupuis and Morgen-
thaler, 2002), a robust estimator simply defined through a weighted score function.
Indeed, although the WMLE is relat...