rmsep_combi: Symmetrized root MSE of Prediction
In OmicsPLS: Data Integration with Two-Way Orthogonal Partial Least Squares

Description Usage Arguments Details Value

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

1	rmsep_combi(Xtst, Ytst, fit)

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

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.

Mean squares difference between predicted Y and true Y

OmicsPLS documentation built on May 19, 2021, 5:08 p.m.