gamlss (version 5.1-4)

plot.gamlss: Plot Residual Diagnostics for an GAMLSS Object

Description

This function provides four plots for checking the normalized (randomized for a discrete response distribution) quantile residuals of a fitted GAMLSS object, referred to as residuals below : a plot of residuals against fitted values, a plot of the residuals against an index or a specific explanatory variable, a density plot of the residuals and a normal Q-Q plot of the residuals. If argument ts=TRUE then the first two plots are replaced by the autocorrelation function (ACF) and partial autocorrelation function (PACF) of the residuals

Usage

# S3 method for gamlss
plot(x, xvar = NULL, parameters = NULL, ts = FALSE, 
           summaries = TRUE, ...)

Arguments

x

a GAMLSS fitted object

xvar

an explanatory variable to plot the residuals against

parameters

plotting parameters can be specified here

ts

set this to TRUE if ACF and PACF plots of the residuals are required

summaries

set this to FALSE if no summary statistics of the residuals are required

...

further arguments passed to or from other methods.

Value

Returns four plots related to the residuals of the fitted GAMLSS model and prints summary statistics for the residuals if the summary=T

Details

This function provides four plots for checking the normalized (randomized) quantile residuals (called residuals) of a fitted GAMLSS object. Randomization is only performed for discrete response variables. The four plots are

• residuals against the fitted values (or ACF of the residuals if ts=TRUE)

• residuals against an index or specified x-variable (or PACF of the residuals if ts=TRUE)

• kernel density estimate of the residuals

• QQ-normal plot of the residuals

For time series response variables option ts=TRUE can be used to plot the ACF and PACF functions of the residuals.

References

Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.

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, http://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 http://www.gamlss.org/).

See Also

gamlss

Examples

# NOT RUN {
data(aids)
a<-gamlss(y~pb(x)+qrt,family=PO,data=aids)
plot(a)
rm(a)
# }