Shortcut sampling function

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.

Usage

rarf(x, n_synth = NULL, ...)

Arguments

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 evidence given. Number of synthetic samples to generate per evidence row if evidence is provided. If NULL, defaults to nrow(x) if no evidence is provided and to 1 otherwise.

...

Extra parameters to be passed to adversarial_rf, forde and forge.

Value

A dataset of n_synth synthetic samples or of nrow(x) synthetic samples if n_synth is undefined.

References

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.

See also

arf, adversarial_rf, forde, forge

Examples

# 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"))