Variable Selection Using MM Algorithms
Variable Selection Using MM Algorithms
About this item
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Author / Creator
Publisher
Hayward, CA: Institute of Mathematical Statistics
Journal title
Language
English
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Publication information
Publisher
Hayward, CA: Institute of Mathematical Statistics
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Scope and Contents
Contents
Variable selection is fundamental to high-dimensional statistical modeling. Many variable selection techniques may be implemented by maximum penalized likelihood using various penalty functions. Optimizing the penalized likelihood function is often challenging because it may be non-differentiable and/or nonconcave. This article proposes a new class...
Alternative Titles
Full title
Variable Selection Using MM Algorithms
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_2674769
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_2674769
Other Identifiers
ISSN
0090-5364
E-ISSN
2168-8966
DOI
10.1214/009053605000000200
