cv.tuning.selection {VARDetect} | R Documentation |
a function to apply cross-validation to select tuning parameter by minimizing SSE
Description
a function to apply cross-validation to select tuning parameter by minimizing SSE
Usage
cv.tuning.selection(data, lambda.seq, mu.seq, alpha_L = 0.25, nfold = 5)
Arguments
data |
a n by p dataset matrix |
lambda.seq |
a numeric vector, indicates the sequence of tuning parameters of sparse components |
mu.seq |
a numeric vector, the sequence of tuning parameters of low rank components |
alpha_L |
a positive numeric value, indicating the constraint space of low rank components |
nfold |
a positive integer, the number of folds for cv |
Value
a list of object, including
- grid
the grid of lamdbas and mus
- lambda
final selected tuning parameter for sparse
- mu
final selected tuning parameter for low rank
[Package VARDetect version 0.1.8 Index]