Shortcut expectation function

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

Usage

earf(x, ...)

Arguments

x

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

...

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

Value

A one row data frame with values for all query variables.

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, expct

Examples

# What is the expected values of each feature?
earf(iris)
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width   Species
#> 1     5.843333    3.057333        3.758    1.199333 virginica

#' # What is the expected values of Sepal.Length?
earf(iris, query = "Sepal.Length")
#>   Sepal.Length
#> 1     5.843333

# What if we condition on Species = "setosa"?
earf(iris, query = "Sepal.Length", evidence = data.frame(Species = "setosa"))
#>   Sepal.Length
#> 1     5.010467