Calculate the stability selection of an SDForest

This function calculates the stability selection of an SDForest (Meinshausen and Bühlmann 2010) . Stability selection is calculated as the fraction of trees in the forest that select a variable for a split at each complexity parameter.

# S3 method for class 'SDForest'
stabilitySelection(object, cp_seq = NULL, verbose = TRUE, ...)

Arguments

object

an SDForest object

cp_seq

A sequence of complexity parameters. If NULL, the sequence is calculated automatically using only relevant values.

verbose

If TRUE progress updates are shown using the `progressr` package. To customize the progress bar, see [`progressr` package](https://progressr.futureverse.org/articles/progressr-intro.html)

...

Further arguments passed to or from other methods.

Value

An object of class paths containing

cp

The sequence of complexity parameters.

varImp_path

A matrix with the stability selection for each complexity parameter.

type

Path type

References

Meinshausen N, Bühlmann P (2010). “Stability Selection.” Journal of the Royal Statistical Society Series B: Statistical Methodology, 72(4), 417–473. ISSN 1369-7412, doi:10.1111/j.1467-9868.2010.00740.x .

See also

plot.paths regPath prune get_cp_seq SDForest

Author

Markus Ulmer

Examples

set.seed(1)
n <- 10
X <- matrix(rnorm(n * 5), nrow = n)
y <- sign(X[, 1]) * 3 + sign(X[, 2]) + rnorm(n)
model <- SDForest(x = X, y = y, Q_type = 'no_deconfounding', nTree = 2, cp = 0.5)
paths <- stabilitySelection(model)
plot(paths)

# \donttest{
plot(paths, plotly = TRUE)

# }