Mixtures of factor analyzers with covariates for modeling multiply censored dependent variables

DOI10.1007/S00362-020-01177-1zbMath1482.62100OpenAlexW3029813318MaRDI QIDQ2062372

Wan-Lun Wang, Wan-Chen Hsieh, Tsung I. Lin, Luis Mauricio Castro

Publication date: 27 December 2021

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-020-01177-1

zbMATH Keywords

detection limitfactor analysiscensored dataAECM algorithmML estimationtruncated multivariate normal distribution

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Point estimation (62F10) Estimation in survival analysis and censored data (62N02)

Related Items (2)

Model-based clustering via mixtures of unrestricted skew normal factor analyzers with complete and incomplete data ⋮ Multivariate Contaminated Normal Censored Regression Model: Properties and Maximum Likelihood Inference

Cites Work

• Algorithm AS 136: A K-Means Clustering Algorithm
• Estimation of Relationships for Limited Dependent Variables
• Initializing the EM algorithm in Gaussian mixture models with an unknown number of components
• Finite mixture modeling of censored regression models
• Pseudo-likelihood estimation of multivariate normal parameters in the presence of left-censored data
• Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
• Choosing initial values for the EM algorithm for finite mixtures
• Finite mixture models and model-based clustering
• Efficient hybrid EM for linear and nonlinear mixed effects models with censored response
• Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy
• Estimating the dimension of a model
• Estimation methods for multivariate Tobit confirmatory factor analysis
• Model-based clustering of censored data via mixtures of factor analyzers
• Multivariate response and parsimony for Gaussian cluster-weighted models
• Robust clustering in regression analysis via the contaminated Gaussian cluster-weighted model
• Maximum likelihood estimation for multivariate skew normal mixture models
• Bayesian inference for shape mixtures of skewed distributions, with application to regression analysis
• Maximum likelihood estimation via the ECM algorithm: A general framework
• Finding Groups in Data
• Estimating Mixtures of Normal Distributions and Switching Regressions
• Algorithms for Model-Based Gaussian Hierarchical Clustering
• Finite mixture models
• Likelihood-based inference for Tobit confirmatory factor analysis using the multivariate Student-\(t\) distribution
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