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Quantile-Based Variable Importance for SPQR / SPQRX

Source: R/SPQRX.R
eval.explain.VI.Rd

Computes variable importance across quantile levels using Quantile Accumulated Local Effects (QALE). Importance is defined as the standard deviation of the ALE function across feature intervals for each quantile level.

Usage

eval.explain.VI(model, x, tau = seq(0.1, 0.9, 0.1), var.indexs = c(1, 2))

Arguments

model

A fitted model object returned by fit_spqrx().

x

Matrix or data frame of covariates used for evaluation.

tau

Numeric vector of quantile levels in (0,1).

var.indexs

Integer vector specifying the indices of variables for which importance is computed.

Value

A matrix of variable importance values. Rows correspond to variables and columns correspond to quantile levels.