resid_density: Density of the residuals in a GAMLLSS model

View source: R/resid_density.R

resid_densityR Documentation

Density of the residuals in a GAMLLSS model

Description

The function resid_density() plots an histogram and a density estimator of the normalised quantile residuals from a fitted GAMLSS model. The function model_density() plots density estimators of the normalised quantile residuals from more than one fitted GAMLSS models.

Usage

resid_density(obj, resid, hist.col = "black", hist.fill = "white", 
              dens.fill = "#FF6666", title)
model_density(obj, ..., title)              

Arguments

obj

The function needs a GAMLSS fitted model or

resid

any standarised residual

hist.col

The colour of the border of the histogram

hist.fill

The colout of the hisogram

dens.fill

the colour of the desnsity

title

A title if needed

...

extra GAMLSS models

Details

This function resid_density() is a denity plot (similar to of the four plots produded when the plotting function plot.gamlss() is used within the gamlss package. I uses plotting function from the ggplot2 package.

Value

A density plot of the residuals is produced.

Author(s)

Mikis Stasinopoulos, Bob Rigby and Fernanda De Bastiani

References

Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, https://www.jstatsoft.org/v23/i07/.

Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.

(see also https://www.gamlss.com/).

See Also

plot.gamlss

Examples

data(abdom)
a<-gamlss(y~pb(x),family=LO,data=abdom)
b<-gamlss(y~pb(x),family=NO,data=abdom)
resid_density(a)
model_density(a,b)

gamlss.ggplots documentation built on Sept. 3, 2023, 5:08 p.m.