Model-based clustering of censored data via mixtures of factor analyzers

DOI10.1016/J.CSDA.2019.06.001zbMath1496.62109OpenAlexW2952610058WikidataQ127639034 ScholiaQ127639034MaRDI QIDQ2337326

Wan-Lun Wang, Victor Hugo Lachos, Luis Mauricio Castro, Tsung I. Lin

Publication date: 19 November 2019

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2019.06.001

zbMATH Keywords

detection limitcensored dataAECM algorithmtruncated multivariate normal distributionoutright clustering

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Censored data models (62N01)

Related Items (11)

Robust clustering of multiply censored data via mixtures of \(t\) factor analyzers ⋮ A flexible factor analysis based on the class of mean-mixture of normal distributions ⋮ An EM algorithm for estimating the parameters of the multivariate skew-normal distribution with censored responses ⋮ Model-based clustering via mixtures of unrestricted skew normal factor analyzers with complete and incomplete data ⋮ Robust factored principal component analysis for matrix-valued outlier accommodation and detection ⋮ Multivariate Contaminated Normal Censored Regression Model: Properties and Maximum Likelihood Inference ⋮ On moments of folded and truncated multivariate Student-\(t\) distributions based on recurrence relations ⋮ Mixtures of factor analyzers with covariates for modeling multiply censored dependent variables ⋮ A skew factor analysis model based on the normal mean–variance mixture of Birnbaum–Saunders distribution ⋮ Finite mixture modeling of censored and missing data using the multivariate skew-normal distribution ⋮ Robust clustering via mixtures of \(t\) factor analyzers with incomplete data

Uses Software

• AS 136
• CensMixReg

Cites Work

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