Monte-Carlo methods for determining optimal number of significant variables. Application to mouse ur...
Monte-Carlo methods for determining optimal number of significant variables. Application to mouse urinary profiles
About this item
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Publisher
Boston: Springer US
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Language
English
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Publisher
Boston: Springer US
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Scope and Contents
Contents
Three methods for variable selection are described, namely the
t
-statistic, Partial Least Squares Discriminant Analysis (PLS-DA) weights and regression coefficients, with the aim of determining which variables are the most significant markers for discriminating between two groups: a variable’s level of significance is related to its magnitud...
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Full title
Monte-Carlo methods for determining optimal number of significant variables. Application to mouse urinary profiles
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Record Identifier
TN_cdi_proquest_miscellaneous_46457391
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_46457391
Other Identifiers
ISSN
1573-3882
E-ISSN
1573-3890
DOI
10.1007/s11306-009-0164-4
