tsmvr_replicate: Replicated k-fold cross-validation for tsmvr

In spcorum/tsmvr-saved: Truly Sparse Multivariate Regression

Description

Calculates the mean and standard deviation of fold-averaged errors derived from replicated tsmvr k-fold cross-validation experiments. The error for each base model is the normalized squared error between the true response and the predicted response on a given cross-validation set.

Usage

tsmvr_replicate(X, Y, s1, s2, pars, quiet = F, seed = NULL)

Arguments

X	design matrix (n-by-p)
Y	response matrix (n-by-q)
s1	regressor matrix sparsity (positive integer)
s2	covariance matrix sparsity (positive integer)
pars	list of algorithm parameters; output of set_parameters
seed	set random seed (integer)
k	number of k-folds (integer greater than 1)
reps	number of replications (positive integer)

Value

A list containing the mean and sd of the error over the replicates as well as the means and standard deviations of the errors across each fold.

Note

See also squared_error, k_folds, tsmvr_solve, tsmvr_cv, and set_parameters.

spcorum/tsmvr-saved documentation built on Nov. 5, 2019, 9:15 a.m.