View source: R/shortcut_functions.R
| rarf | R Documentation | 
Calls adversarial_rf, forde and forge.
For repeated application, it is faster to save outputs of adversarial_rf
and forde and pass them via ... or directly use forge.
rarf(x, n_synth = NULL, ...)
| x | Input data. Integer variables are recoded as ordered factors with a warning. See Details. | 
| n_synth | Number of synthetic samples to generate for unconditional
generation with no  | 
| ... | Extra parameters to be passed to  | 
A dataset of n_synth synthetic samples or of nrow(x) synthetic
samples if n_synth is undefined.
Watson, D., Blesch, K., Kapar, J., & Wright, M. (2023). Adversarial random forests for density estimation and generative modeling. In Proceedings of the 26th International Conference on Artificial Intelligence and Statistics, pp. 5357-5375.
arf, adversarial_rf, forde, forge
# Generate 150 (size of original iris dataset) synthetic samples from the iris dataset
x_synth <- rarf(iris)
# Generate 100 synthetic samples from the iris dataset
x_synth <- rarf(iris, n_synth = 100)
# Condition on Species = "setosa"
x_synth <- rarf(iris, evidence = data.frame(Species = "setosa"))
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