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Which covariates a jackknife would drop

Source: R/jackknife.R
jackknife_dropped.Rd

The keep list and min_predictors floor applied to the test result. Split out from the run so a report-only jackknife can still say what dropping would have removed, which is the number worth seeing before turning drop on.

Usage

jackknife_dropped(jk, settings = attr(jk, "settings"))

Arguments

jk

the result of jackknife_covariates()

settings

from jackknife_settings(). Defaults to the settings the jackknife was actually run under, which it carries on itself — so asking a result what it would drop needs nothing but the result.

Value

a character vector of covariate names, possibly empty

Details

When the floor binds, the covariates kept are the ones that contributed most, so a run that would have dropped everything keeps the best of a bad set rather than an arbitrary one.

See also

jackknife_covariates()

Examples

jk <- data.frame(
  variable = c("SST", "SSS", "CHL"),
  contribution = c(0.08, 0.001, 0.0005),
  significant = c(TRUE, FALSE, FALSE)
)
settings <- list(keep = character(), min_predictors = 2)
jackknife_dropped(jk, settings)      # only the weakest: the floor binds at 2
#> [1] "CHL"

jackknife_dropped(jk, list(keep = "CHL", min_predictors = 1))
#> [1] "SSS"