Predict with an instrumental forest
Gets estimates of tau(x) using a trained instrumental forest.
## S3 method for class 'instrumental_forest' predict( object, newdata = NULL, num.threads = NULL, estimate.variance = FALSE, ... )
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). |
Vector of predictions, along with (optional) variance estimates.
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