An EM algorithm for fitting matrix-variate normal distributions on interval-censored and missing data
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DOI: 10.1007/s11222-025-10575-0
Abstract: Matrix-variate distributions are powerful tools for modeling three-way datasets that often arise in longitudinal and multidimensional spatio-temporal studies. However, observations in these datasets can be missing or subject to some detection limits because of the… read more here.
Keywords: censored missing; matrix variate; variate normal; missing data ... See more keywords
GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies
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DOI: 10.1371/journal.pcbi.1005973
Abstract: Left-censored missing values commonly exist in targeted metabolomics datasets and can be considered as missing not at random (MNAR). Improper data processing procedures for missing values will cause adverse impacts on subsequent statistical analyses. However,… read more here.
Keywords: censored missing; left censored; value imputation; missing value ... See more keywords