spvim_se: Standard error estimate for SPVIM values

In bdwilliamson/nova: Perform Inference on Algorithm-Agnostic Variable Importance

Standard error estimate for SPVIM values

Description

Compute standard error estimates based on the estimated influence function for a SPVIM value of interest.

Usage

spvim_se(ics, idx = 1, gamma = 1, na_rm = FALSE)

Arguments

ics	the influence function estimates based on the contributions from sampling observations and sampling subsets: a list of length two resulting from a call to spvim_ics.
idx	the index of interest
gamma	the proportion of the sample size used when sampling subsets
na_rm	remove NAs?

Details

Since the processes for sampling observations and subsets are independent, the variance for a given SPVIM estimator is simply the sum of the variances based on sampling observations and on sampling subsets.

Value

The standard error estimate for the desired SPVIM value

See Also

spvim_ics for how the influence functions are estimated.

bdwilliamson/nova documentation built on Feb. 1, 2024, 10:04 p.m.