Set the evals of an aba model — set

Evals are the ways in which you fit your stats on the data. The standard method is to simply fit the model on the entire dataset one time. However, there are additional methods such as bootstrap sampling, train-test splits, and cross validation. An aba model can have multiple evals, which can be useful if you want to test the difference between cross validation with five splits or three, for example.

Usage

set_evals(.model, ..., .labels = NULL)

Arguments

.model: aba model. The model to set the evals for.
...: comma-separated strings or abaEval objects. The evals you wish to set for the given model
.labels: vector of strings (optional). The .labels for each eval.

Value

aba model with evals set.

Examples

model <- aba_model() %>%
  set_evals(
    'standard'
    #'boot',
    #'traintest',
    #'cv'
  )
model <- aba_model() %>%
  set_evals(
    eval_standard()
    #eval_boot(ntrials = 100),
    #eval_traintest(split = 0.5, ntrials = 10),
    #eval_cv(nfolds = 3, ntrials = 10)
  )
model <- aba_model() %>%
  set_evals(
    eval_cv(nfolds = 3)
  )