cv_predict: Out of Sample Predictions Using Cross Valiation
In wlattner/hete: Heterogeneous Treatment Effect Modeling

Description Usage Arguments

View source: R/cross_validation.R

Out of Sample Predictions Using Cross Valiation

cv_predict(x, ...)

## Default S3 method:
cv_predict(x, y, tmt, model, folds = 3, ...)

## S3 method for class 'formula'
cv_predict(x, data, model, folds = 3, ...)

`x`	a `data.frame` or matrix with predictor variables measured prior to treatment or unaffected by treatment. Alternatively, this can be a model formula: `outcome ~ x1 + x2 \| treatment`
`...`	extra parameters passed to `model`.
`y`	a vector of outcomes.
`tmt`	a vector indicating which units received treatment.
`model`	a `hete_model` to use for making predictions. are passed to the `model` fitting function.
`folds`	the number of folds to use for cros validation.
`data`	a `data.frame` containing the variables specified in `x` when using a formula to specify the model.