vibe.lm: Variable Importance calculation for an 'lm' object

In Stan125/vibe: Variable Importance Beyond Linear Models

Variable Importance calculation for an lm object

Description

vibe.lm takes a fitted lm() object and calculates variable importance metrics by fitting the submodels required, extracting the desired goodness-of-fit metric and applying variable importance metrics to it.

Usage

## S3 method for class 'lm'
vibe(object, varimp = "hp", gof = "R2e", ncores = 1, progress = TRUE, ...)

Arguments

object	A lm object, typically result of lm().
varimp	One of c("hp", "relweights"), which stand for hierarchical partitioning and relative weights.
gof	Goodness-of-fit metric, the changes of which shall be analysed
ncores	Number of cores used for the model fitting process, happening in part_core.
progress	Boolean. Do you want to see a progress bar?
...	Other arguments

Examples

iris_lm <- lm(Sepal.Width ~ ., data = iris)
vibe(iris_lm, gof = "R2Mac", varimp = "hp")

Stan125/vibe documentation built on June 6, 2024, 11:36 a.m.