R: Predict with an instrumental forest

predict.instrumental_forest {grf} | R Documentation

## Predict with an instrumental forest

### Description

Gets estimates of tau(x) using a trained instrumental forest.

### Usage

    ## S3 method for class 'instrumental_forest'
    predict(object, newdata = NULL,
      num.threads = NULL, estimate.variance = FALSE, ...)

### Arguments

`object` | The trained forest.
`newdata` | Points at which predictions should be made. If NULL, makes out-of-bag predictions on the training set instead (i.e., provides predictions at Xi using only trees that did not use the i-th training example). Note that this matrix should have the number of columns as the training matrix, and that the columns must appear in the same order.
`num.threads` | Number of threads used in training. If set to NULL, the software automatically selects an appropriate amount.
`estimate.variance` | Whether variance estimates for hattau(x) are desired (for confidence intervals).
`...` | Additional arguments (currently ignored).

### Value

Vector of predictions, along with (optional) variance estimates.

[Package grf version 1.0.0 Index]