Usage
## S3 method for class 'factor':
cv(y, formula, data, model, predict, k=10, random=TRUE,
strat=FALSE,
predictions=NULL, getmodels=NULL, list.tindx = NULL, \dots)Arguments
y
response variable, either of class factor
(classification), numeric (regression) or Surv (survival).
data
data frame of predictors and response described in formula.
model
a function implementing the predictive model to be
evaluated. The function model can either return an
object representing a fitted model or a function with
argument newdata which returns predicted va
predict
a function with arguments object and newdata
only which predicts the status of the observations in newdata based
on the fitted model in object.
k
k-fold cross-validation.
random
logical, indicates whether a random order or the given
order of the data should be used for sample splitting or not, defaults to
TRUE.
strat
logical, stratified sampling or not, defaults to FALSE.
predictions
logical, return the prediction of each observation.
getmodels
logical, return a list of models for each fold.
list.tindx
list of numeric vectors, indicating which
observations are included in each cross-validation sample.
...
additional arguments to model.