Variable selection with Minimal Depth (MD).

This is identical to [SurrogateMinimalDepth()], except it requires `s` to be 0.

Usage

MinimalDepth(RFS)

Arguments

RFS

A [RandomForestSurrogates()] object with `s` equal to 0.

Value

A `MinimalDepth` S3 list object: - `RFS`: The original [RandomForestSurrogates()] object. - `selected`: A character vector of the selected variable names. - `depth`: A numeric vector of the surrogate minimal depth for each variable. - `threshold`: The depth threshold used to select variables. - `surrogates`: - `average`: Total average number of surrogate variables. - `layer`: Average number of surrogate variables by layer (Named numeric of length 1000).

References

- Ishwaran, H. et al. (2011) Random survival forests for high-dimensional data. Stat Anal Data Min, 4, 115–132. <https://onlinelibrary.wiley.com/doi/abs/10.1002/sam.10103> - Ishwaran, H. et al. (2010) High-Dimensional Variable Selection for Survival Data. J. Am. Stat. Assoc., 105, 205–217. <http://www.ccs.miami.edu/~hishwaran/papers/IKGML.JASA.2010.pdf>

Examples

# \donttest{
data("SMD_example_data")

res.md <- MinimalDepth(RandomForestSurrogates(
  x = SMD_example_data[, -1],
  y = SMD_example_data[, 1],
  num.trees = 10,
  s = 0,
  num.threads = 1
))
#> Warning: `seed` was not set. Your results may not be reproducible.
# }