R Graphical Manual

Last data update: 2014.03.03

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R Release (3.2.3)
CranContrib
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Results 1 - 6 of 6 found.
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predict.plr (Package: stepPlr) :

This function computes the linear predictors, probability estimates, or the class labels for new data, using a plr object.

● Data Source: CranContrib
● Keywords: models, regression
● Alias: predict.plr
● 0 images

plr (Package: stepPlr) :

This function fits a logistic regression model penalizing the size of the L2 norm of the coefficients.

● Data Source: CranContrib
● Keywords: models, regression
● Alias: plr
● 0 images

predict.stepplr (Package: stepPlr) :

This function computes the linear predictors, probability estimates, or the class labels for new data, using a stepplr object.

● Data Source: CranContrib
● Keywords: models, regression
● Alias: predict.stepplr
● 0 images

step.plr (Package: stepPlr) :

This function fits a series of L2 penalized logistic regression models selecting variables through the forward stepwise selection procedure.

● Data Source: CranContrib
● Keywords: models, regression
● Alias: step.plr
● 0 images

plr-internal (Package: stepPlr) :

Internal plr functions

● Data Source: CranContrib
● Keywords: internal
● Alias: anova.stepplr, cross.imat, get.imat, imat, print.plr, print.stepplr, summary.plr, summary.stepplr, term.match
● 0 images

cv.step.plr (Package: stepPlr) :

This function computes cross-validated deviance or prediction errors for step.plr. The parameters that can be cross-validated are lambda and cp.

● Data Source: CranContrib
● Keywords: models, regression
● Alias: cv.step.plr
● 0 images