A function to choose optimal number of eigenfunctions via Cross-Validation
Usage
cvfunOnFun(seed, predictor, response, actual, folds = 10)
Arguments
- seed
Seed for reproducibility
- predictor
An object of class irregMFPCA corresponding to the predictor
- response
An object of class irregMFPCA corresponding to the response
- actual
A data frame with the actual values of the response
- folds
Number of folds for cross-validation. Default is 10
Value
A matrix of mean squared errors for each combination of number of eigenfunctions