cv.tuning.selection {VARDetect}R Documentation

a function to apply cross-validation to select tuning parameter by minimizing SSE

Description

a function to apply cross-validation to select tuning parameter by minimizing SSE

Usage

cv.tuning.selection(data, lambda.seq, mu.seq, alpha_L = 0.25, nfold = 5)

Arguments

data

a n by p dataset matrix

lambda.seq

a numeric vector, indicates the sequence of tuning parameters of sparse components

mu.seq

a numeric vector, the sequence of tuning parameters of low rank components

alpha_L

a positive numeric value, indicating the constraint space of low rank components

nfold

a positive integer, the number of folds for cv

Value

a list of object, including

grid

the grid of lamdbas and mus

lambda

final selected tuning parameter for sparse

mu

final selected tuning parameter for low rank


[Package VARDetect version 0.1.8 Index]