Some parameters that control the behaviour of `errorest`

.

```
control.errorest(k = 10, nboot = 25, strat = FALSE, random = TRUE,
predictions = FALSE, getmodels=FALSE, list.tindx = NULL)
```

A list with the same components as arguments.

- k
integer, specify $k$ for $k$-fold cross-validation.

- nboot
integer, number of bootstrap replications.

- strat
logical, if

`TRUE`

, cross-validation is performed using stratified sampling (for classification problems).- random
logical, if

`TRUE`

, cross-validation is performed using a random ordering of the data.- predictions
logical, indicates whether the prediction for each observation should be returned or not (classification and regression only). For a bootstrap based estimator a matrix of size 'number of observations' times nboot is returned with predicted values of the ith out-of-bootstrap sample in column i and 'NA's for those observations not included in the ith out-of-bootstrap sample.

- getmodels
logical, indicates a list of all models should be returned. For cross-validation only.

- list.tindx
list of numeric vectors, indicating which observations are included in each bootstrap or cross-validation sample, respectively.