Man pages for multiridge
Fast Cross-Validation for Multi-Penalty Ridge Regression

augmentAugment data with zeros.
betasoutCoefficient estimates from (converged) IWLS fit
createXblocksCreate list of paired data blocks
createXXblocksCreates list of (unscaled) sample covariance matrices
CVfoldsCreates (repeated) cross-validation folds
CVscoreCross-validated score
dataXXmirmethContains R-object 'dataXXmirmeth'
doubleCVDouble cross-validation for estimating performance of...
fastCV2Fast cross-validation per data block
IWLSCoxridgeIterative weighted least squares algorithm for Cox ridge...
IWLSridgeIterative weighted least squares algorithm for linear and...
mgcv_lambdaMaximum marginal likelihood score
mlikCVOuter-loop cross-validation for estimating performance of...
multiridge-packageFast cross-validation for multi-penalty ridge regression
optLambdasFind optimal ridge penalties.
optLambdas_mgcvFind optimal ridge penalties with maximimum marginal...
optLambdas_mgcvWrapFind optimal ridge penalties with sequential optimization.
optLambdasWrapFind optimal ridge penalties with sequential optimization.
predictIWLSPredictions from ridge fits
ScoringEvaluate predictions
setupParallelSetting up parallel computing
SigmaFromBlocksCreate penalized sample cross-product matrix
multiridge documentation built on June 15, 2021, 9:08 a.m.