distributional_effects: Calculate distributional effects

In be-green/quantspace: Quantile Regression via Quantile Spacing

Calculate distributional effects

Description

Calculate distributional effects

Usage

distributional_effects(object, tails = "gaussian", ...)

## S3 method for class 'qs'
distributional_effects(object, tails = "gaussian", newdata = NULL, ...)

## S3 method for class 'matrix'
distributional_effects(object, tails, alphas, ...)

Arguments

object	fit of class qs or matrix of fitted quantiles
tails	one of "gaussian" or "exponential"
...	other parameters to pass
newdata	new data to predict distributional outcomes for
alphas	which quantiles these were fitted at

Details

The arguments alphas and quantiles are automatically handled if you pass an object of class "qs". If you don't pass new data to be predicted on, it will assume that you want to calculate distributional effects at the average of the data. This varies because of the non-linear model for the quantile process

be-green/quantspace documentation built on March 20, 2024, 5:30 p.m.