resemble (version 1.2.2)

pgpcv_cpp: Internal Cpp function for performing leave-group-out cross validations for pls regression

Description

For internal use only!.

Usage

pgpcv_cpp(X, Y, mindices, pindices, noisev = 0.001, scale)

Arguments

X

a matrix of predictor variables.

Y

a matrix of a single response variable.

mindices

a matrix with n rows and m columns where m is equivalent to the number of resampling iterations. The elements of each column indicate the indices of the samples to be used for modeling at each iteration.

pindices

a matrix with k rows and m columns where m is equivalent to the number of resampling iterations. The elements of each column indicate the indices of the samples to be used for predicting at each iteration.

scale

a logical indicating whether both the predictors and the response variable must be scaled to zero mean and unit variance.

mindices

a matrix with n rows and m columns where m is equivalent to the number of resampling iterations. The elements of each column indicate the indices of the samples to be used for modeling at each iteration.

pindices

a matrix with k rows and m columns where m is equivalent to the number of resampling iterations. The elements of each column indicate the indices of the samples to be used for predicting at each iteration.

ncomp

an integer indicating the number of pls components.

Value

a list containing the following one-row matrices:

• rmse.seg the RMSEs.
• st.rmse.seg the standardized RMSEs.
• rsq.seg the coefficients of determination.