dhglm (version 2.0)

plotdhglm: Produce Model-Checking Plots for a Double Hierarchical Generalized Linear Model Analysis

Description

Plots residuals for the mean and dispersion models

Usage

plotdhglm(OUTPUT, type="mean", random=NULL)

Arguments

OUTPUT

The <dhglmfit> object to be plotted

type

Type of model required (mean, dispersion)

random

Random term whose residuals are to be plotted (mean, phi, v, alpha). Default (NULL) is the residuals from the full model

Details

Four types of plot are available (normal probability plot for residuals, histogram of residuals, residuals versus fitted values and absolute values of residuals versus fitted values).

See Also

<dhglmfit>

Examples

# NOT RUN {
#### Model checking plot for crack-growth data
data(crack_growth)
model_mu<-DHGLMMODELING(Model="mean", Link="log", 
LinPred=y~crack0+(1|specimen),RandDist="inverse-gamma")
model_phi<-DHGLMMODELING(Model="dispersion", Link="log", 
LinPred=phi~cycle+(1|specimen),RandDist="gaussian")
res_crack_dhglm1<-dhglmfit(RespDist="gamma", DataMain=crack_growth, 
MeanModel=model_mu, DispersionModel=model_phi,Maxiter=1)
plotdhglm(res_crack_dhglm1)
# }