Calculate distributional effects

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

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

# S3 method for 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