Package ‘leaps’ - R
Package leaps January 16, 2020TitleRegression Subset Lumley based on Fortran code by Alan MillerDescriptionRegression subset selection, including exhaustive (>= 2)MaintainerThomas 17:50:05 UTCRtopics documented:leaps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4regsubsets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5Index8leapsall-subsets regressiomDescriptionleaps() performs an exhaustive search for the best subsets of the variables in x for predicting y inlinear regression, using an efficient branch-and-bound algorithm. It is a compatibility wrapper forregsubsetsdoes the same thing the algorithm returns a best model of each size, the results do not depend on a penalty modelfor model size: it doesn t make any difference whether you want to use AIC, BIC, CIC, DIC.
leaps() performs an exhaustive search for the best subsets of the variables in x for predicting y in linear regression, using an efficient branch-and-bound algorithm. It is a compatibility wrapper for
Download Package ‘leaps’ - R
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: