bestSubsetSearch: Evaluate information criteria for best subset selection
In GabrielHoffman/mvIC: Multivariate Information Criteria to identify important predictors in high dimensional multivariate regression
bestSubsetSearch R Documentation
Evaluate information criteria for best subset selection
Description
Evaluate information criteria for best subset selection
Usage
bestSubsetSearch(Y, data, variables, maxk = 5)
Arguments
Y
response matrix with responses ad columns and samples as rows
data
data.frame with columns corresponding to formula
variables
array of variable names to be considered in the regression. Random effects are not allowed
maxk
evaluate all combinations of variables up to size maxk
GabrielHoffman/mvIC documentation built on Aug. 30, 2022, 7:58 p.m.
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| bestSubsetSearch | R Documentation |
Evaluate information criteria for best subset selection
Description
Evaluate information criteria for best subset selection
Usage
bestSubsetSearch(Y, data, variables, maxk = 5)
Arguments
Y |
response matrix with responses ad columns and samples as rows |
data |
data.frame with columns corresponding to formula |
variables |
array of variable names to be considered in the regression. Random effects are not allowed |
maxk |
evaluate all combinations of variables up to size maxk |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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