Compute the value of the influence function for the given group of left-out covariates.
vimp_update(
full,
reduced,
y,
folds = folds,
weights = rep(1, length(y)),
type = "r_squared",
na.rm = FALSE
)fitted values from a regression of the outcome on the full set of covariates.
fitted values from a regression either (1) of the outcome on the reduced set of covariates, or (2) of the fitted values from the full regression on the reduced set of covariates.
the outcome.
the folds for hypothesis testing.
weights for the computed influence curve (e.g., inverse probability weights for coarsened-at-random settings)
which parameter are you estimating (defaults to anova, for ANOVA-based variable importance)?
logical; should NAs be removed in computation? (defaults to FALSE)
The influence function values for the given group of left-out covariates.
See the paper by Williamson, Gilbert, Simon, and Carone for more details on the mathematics behind this function and the definition of the parameter of interest.