rmsep_combi: Symmetrized root MSE of Prediction

In selbouhaddani/OmicsPLS: Data Integration with Two-Way Orthogonal Partial Least Squares

Symmetrized root MSE of Prediction

Description

Calculates the symmetrized root MSE of prediction on test data. *Expected* to work in combination with loocv.

Usage

rmsep_combi(Xtst, Ytst, fit)

Arguments

Xtst	Numeric vector or matrix.
Ytst	Numeric vector or matrix.
fit	o2m fit (on data without Xtst and Ytst).

Details

This function is the building block for loocv, as it produced the prediction error for test (left out) data.

This is a symmetrized version of rmsep, and is used by loocv. The predicion error of both Xtst and Ytst are calculated and summed. Whether this is a good idea depends: If X and Y have similar meanings (LC-MS versus MALDI) this is a good thing to do. If the two matrices do not have similar meanings, (Metabolomics versus Transcriptomics) then you may want to not sum up the two prediction errors or include weights in the sum.

Value

Mean squares difference between predicted Y and true Y

selbouhaddani/OmicsPLS documentation built on Aug. 25, 2022, 9:52 p.m.