summary.CV.twostageSL: Summary Function For Cross-Validated Two stage Super Learner

In wuziyueemory/twostageSL: Two-Stage Super Learner Prediction Function

Description

Summary method for the CV.twostageSL function

Usage

## S3 method for class 'CV.twostageSL'
summary(object, obsWeights = NULL, ...)

## S3 method for class 'summary.CV.twostageSL'
print(x, digits = max(2, getOption("digits") - 2), ...)

Arguments

object	An object of class CV.twostageSL, the result of a call to CV.twostageSL.
obsWeights	Optional vector for observation weights.
...	additional arguments …
x	An object of class summary.CV.twostageSL, the result of a call to summary.CV.twostageSL.
digits	The number of significant digits to use when printing.

Details

Summary method for CV.twostageSL. Calculates the V-fold cross-validated estimate of either the mean squared error or the -2*log(L) depending on the loss function used.

Value

summary.CV.twostageSL returns a list with components

call	The function call from CV.twostageSL.
method	Describes the loss function used. Currently default is CC.LS.scale.
V	Number of folds.
Risk.SL	Risk estimate for the two stage super learner.
Risk.dSL	Risk estimate for the discrete super learner (the cross-validation selector).
Risk.library	A matrix with the risk estimates for each algorithm in the library.
Table	A table with the mean risk estimate and standard deviation across the folds for the two stage super learner and all algorithms in the library.

Author(s)

Ziyue Wu

See Also

CV.twostageSL

wuziyueemory/twostageSL documentation built on Oct. 19, 2020, 3:45 p.m.