Simplex Factor Models for Multivariate Unordered Categorical Data

DOI10.1080/01621459.2011.646934zbMath1263.62097OpenAlexW2036533305WikidataQ30658832 ScholiaQ30658832MaRDI QIDQ4916469

Anirban Bhattacharya, David B. Dunson

Publication date: 22 April 2013

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3728016

zbMATH Keywords

ClassificationMutual informationFactor analysisContingency tableLatent variableNonnegative tensor factorizationNonparametric BayesPolytomous regression

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Bayesian inference (62F15) Numerical analysis or methods applied to Markov chains (65C40)

Related Items

Multivariate mixed membership modeling: inferring domain-specific risk profiles, Composite mixture of log-linear models with application to psychiatric studies, Bayesian inference on group differences in multivariate categorical data, Bayesian semiparametric analysis for two-phase studies of gene-environment interaction, Prediction and Inference With Missing Data in Patient Alert Systems, Bayesian Modeling of Temporal Dependence in Large Sparse Contingency Tables, Longitudinal mixed membership trajectory models for disability survey data, Loglinear model selection and human mobility, Modeling association in microbial communities with clique loglinear models, Fast Moment Estimation for Generalized Latent Dirichlet Models, Exploring dependence between categorical variables: benefits and limitations of using variable selection within Bayesian clustering in relation to log-linear modelling with interaction terms, Probabilistic archetypal analysis

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Efficient Bayesian inference for Gaussian copula regression models
• The mode oriented stochastic search (MOSS) algorithm for log-linear models with conjugate priors
• Copula Gaussian graphical models and their application to modeling functional disability data
• Nonnegative ranks, decompositions, and factorizations of nonnegative matrices
• A conjugate prior for discrete hierarchical log-linear models
• Hyper Markov laws in the statistical analysis of decomposable graphical models
• Prior distributions on spaces of probability measures
• Sparse graphical models for exploring gene expression data
• Generalized latent trait models
• Experiments in stochastic computation for high-dimensional graphical models
• Three centuries of categorical data analysis: Log-linear models and maximum likelihood estima\-tion
• Describing disability through individual-level mixture models for multivariate binary data
• A Bayesian analysis of some nonparametric problems
• Nonparametric Bayesian models through probit stick-breaking processes
• Orthogonal Tensor Decompositions
• Nonparametric Bayes Conditional Distribution Modeling With Variable Selection
• Hierarchical Dirichlet Processes
• Likelihood inference in a correlated probit regression model
• Bayesian curve fitting using multivariate normal mixtures
• Analysis of multivariate probit models
• Dynamic Latent Trait Models for Multidimensional Longitudinal Data
• A Multilinear Singular Value Decomposition
• 10.1162/153244303322533214
• 10.1162/jmlr.2003.3.4-5.993
• Exploratory latent structure analysis using both identifiable and unidentifiable models
• Gibbs Sampling Methods for Stick-Breaking Priors
• Bayesian Graphical Models for Discrete Data
• Nonparametric Bayes Modeling of Multivariate Categorical Data
• High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics
• Bayesian Density Regression
• Polychotomous quantal response by maximum indicant
• Order-Based Dependent Dirichlet Processes
• Random forests