# Calculate sparse principal components of time-dependent variation on cross-validation

Source:`R/zeitzeiger_cv.R`

`zeitzeigerSpcCv.Rd`

Calculate SPCs for each fold of cross-validation.

## Usage

```
zeitzeigerSpcCv(
fitResultList,
nTime = 10,
useSpc = TRUE,
sumabsv = 1,
orth = TRUE,
dopar = TRUE
)
```

## Arguments

- fitResultList
Output of

`zeitzeigerFitCv()`

.- nTime
Number of time-points by which to discretize the time-dependent behavior of each feature. Corresponds to the number of rows in the matrix for which the SPCs will be calculated.

- useSpc
Logical indicating whether to use

`SPC`

(default) or`svd`

.- sumabsv
L1-constraint on the SPCs, passed to

`SPC`

.- orth
Logical indicating whether to require left singular vectors be orthogonal to each other, passed to

`SPC`

.- dopar
Logical indicating whether to process the folds in parallel. Use

`doParallel::registerDoParallel()`

to register the parallel backend.

## Value

A list consisting of the result from `zeitzeigerSpc()`

for each fold.