GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies

Title
GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies
Authors
Keywords
Metabolomics, Forecasting, Normal distribution, Data processing, Simulation and modeling, Statistical data, Multivariate analysis, Principal component analysis
Journal
PLoS Computational Biology
Volume 14, Issue 1, Pages e1005973
Publisher
Public Library of Science (PLoS)
Online
2018-02-01
DOI
10.1371/journal.pcbi.1005973

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