cv.tuning.selection function

a function to apply cross-validation to select tuning parameter by minimizing SSE

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

Returns

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