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Variable Selection in Heterogeneous Datasets: A Truncated-rank Sparse Linear Mixed Model with Applications to Genome-wide Association Studies

A fundamental and important challenge in modern datasets of ever increasing dimensionality is variable selection, which has taken on renewed interest recently due to the growth of biological and medical datasets with complex, non-i.i.d. structures. Naïvely applying classical variable selection metho...

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Podrobná bibliografie
Vydáno v:Proceedings (IEEE Int Conf Bioinformatics Biomed)
Hlavní autoři: Wang, Haohan, Aragam, Bryon, Xing, Eric P.
Médium: Artigo
Jazyk:Inglês
Vydáno: 2017
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC5889139/
https://ncbi.nlm.nih.gov/pubmed/29629235
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/BIBM.2017.8217687
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