The Monte Carlo EM method for estimating multivariate tobit latent variable models
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Publication:3401364
DOI10.1080/00949650802137170zbMath1179.62081OpenAlexW2093843251MaRDI QIDQ3401364
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Publication date: 29 January 2010
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949650802137170
maximum likelihood estimatesGibbs samplerfactor analysislatent variableMCEM algorithmmultivariate tobit model
Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12) Monte Carlo methods (65C05)
Related Items (2)
Estimation methods for multivariate Tobit confirmatory factor analysis ⋮ Likelihood-based inference for Tobit confirmatory factor analysis using the multivariate Student-\(t\) distribution
Cites Work
- Estimation of Relationships for Limited Dependent Variables
- Tobit models: A survey
- On the convergence properties of the EM algorithm
- Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions
- Factor analysis and AIC
- Bayes inference in the Tobit censored regression model
- Estimating the dimension of a model
- Posterior simulation and Bayes factors in panel count data models
- Factor models for multivariate count data.
- A Monte Carlo EM method for estimating multinomial probit models.
- Factor analysis for clustered observations
- Measurement invariance, factor analysis and factorial invariance
- Estimation of the SUR Tobit model via the MCECM algorithm.
- Maximum likelihood estimation via the ECM algorithm: A general framework
- Maximum Likelihood Estimation from Incomplete Data
- Practical Markov Chain Monte Carlo
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- Generalized Least Squares with an Estimated Autocovariance Matrix
- Analysis of multivariate probit models
- Maximum Likelihood Variance Components Estimation for Binary Data
- High-Dimensional Multivariate Probit Analysis
- Fitting Full-Information Item Factor Models and an Empirical Investigation of Bridge Sampling
- Tools for statistical inference. Methods for the exploration of posterior distributions and likelihood functions.
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