dot-cv: Cross-validation

In palasso: Sparse Regression with Paired Covariates

Cross-validation

Description

Repeatedly leaves out samples, and predicts their response.

Usage

.cv(y, x, foldid, lambda, args)

Arguments

y	response: vector of length n
x	covariates: matrix with n rows (samples) and k * p columns (variables)
foldid	fold identifiers: vector of length n, with entries from 1 to nfolds
lambda	lambda sequence: vector of decreasing positive values
args	options for paired lasso: list of arguments (output from .dims and .args)

Value

Returns matrix of predicted values (except "cox")

Examples

NA

palasso documentation built on Sept. 30, 2024, 9:30 a.m.