Missing value imputation in high-dimensional phenomic data: imputable or not, and how?
Missing value imputation in high-dimensional phenomic data: imputable or not, and how?
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Publisher
England: BioMed Central Ltd
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Language
English
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Publisher
England: BioMed Central Ltd
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Scope and Contents
Contents
In modern biomedical research of complex diseases, a large number of demographic and clinical variables, herein called phenomic data, are often collected and missing values (MVs) are inevitable in the data collection process. Since many downstream statistical and bioinformatics methods require complete data matrix, imputation is a common and practi...
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Full title
Missing value imputation in high-dimensional phenomic data: imputable or not, and how?
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4228077
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4228077
Other Identifiers
ISSN
1471-2105
E-ISSN
1471-2105
DOI
10.1186/s12859-014-0346-6
