Shortcut likelihood function

Calls adversarial_rf, forde and lik. For repeated application, it is faster to save outputs of adversarial_rf and forde and pass them via ... or directly use lik.

Usage

darf(x, query = NULL, ...)

Arguments

x

Input data. Integer variables are recoded as ordered factors with a warning. See Details.

query

Data frame of samples, optionally comprising just a subset of training features. See Details of lik. Is set to x if zero.

...

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

Value

A vector of likelihoods, optionally on the log scale. 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

# Estimate log-likelihoods
ll <- darf(iris)

# Partial evidence query
ll <- darf(iris, query = iris[1, 1:3])

# Condition on Species = "setosa"
ll <- darf(iris, query = iris[1, 1:3], evidence = data.frame(Species = "setosa"))