res.check: Diagnostic plots for discrete/continuous response margins

In GJRM: Generalised Joint Regression Modelling

Diagnostic plots for discrete/continuous response margins

Description

It produces diagnostic plots based on (randomised) quantile residuals.

Usage

res.check(x, intervals = FALSE, n.sim = 100, prob.lev = 0.05, ...)

Arguments

x	A fitted gjrm object.
intervals	If TRUE then intervals for the qqplots are produced.
n.sim	Number of replicate datasets used to simulate quantiles of the residual distribution.
prob.lev	Overall probability of the left and right tails of the probabilities' distributions used for interval calculations.
...	Graphics parameters to pass on to plotting commands.

Details

If the model fits the response well then the plots should look normally distributed. When fitting models with discrete and/or continuous margins, four plots will be produced. In this case, the arguments main2 and xlab2 come into play and allow for different labelling across the plots.

Value

qr	It returns the (randomised) quantile residuals for the continuous or discrete margin when fitting a model that involves a binary response.
qr1	As above but for first equation (this applies when fitting models with continuous/discrete margins).
qr2	As above but for second equation.

Author(s)

Maintainer: Giampiero Marra [e-mail]

See Also

gjrm

GJRM documentation built on Oct. 25, 2024, 5:07 p.m.