boot: Parametric bootstrap for LMLS

In hriebl/lmls: Gaussian Location-Scale Regression

Description

A simple parametric bootstrap algorithm for location-scale regression models from the lmls() function.

Usage

boot(m, num_samples = 1000, seed = NULL)

Arguments

m	A location-scale regression model from the lmls() function.
num_samples	The number of bootstrap samples to draw.
seed	Either NULL or an integer that will be used in a call to set.seed() before simulating the response vectors.

Value

An lmls S3 object, see lmls(). The entry boot with the matrices of bootstrap samples is added to the object as a list with the names location and scale.

Examples

library(lmls)
m <- lmls(y ~ poly(x, 2), ~ x, data = abdom, light = FALSE)
m <- boot(m)
summary(m, type = "boot")
hist(m$boot$scale[, 2])

hriebl/lmls documentation built on Jan. 18, 2022, 2:41 p.m.