plot_envelope: Plot Envelope

In wjunger/ares: Environmental air pollution epidemiology: a library for time series analysis

Description

Plot a simulated envelope of the residuals

Usage

plot_envelope(x, rep = 39, type = "deviance", new = TRUE, ...)

Arguments

x	a model fitted by fit_core
rep	an integer indicating the number of replications. Default is 19. See Details
type	a quoted string indicating the type of residuals to extract. Default is "deviance". See get_residuals
new	if TRUE a new graph window is opened
...	further options for qqnorm

Details

This function implements a simulated envelope of residuals. It is a plot to check if the normality assumptions of the residuals hold. Although the authors originally suggested 39 replications, at least a hundred may be reasonable, since the processing power of modern computers is no longer a limitation. However, the re-sampling strategy of the method is still time consuming.

The algorithm is implemented for Poisson family models only. Although it supports quasi-poisson models, the results may be inaccurate.

Value

This function does not return a value.

Author(s)

Washington Junger [e-mail] and Antonio Ponce de Leon [e-mail]

References

McGullagh, P., Nelder, J. A. (1989) Generalized linear models. Chapman and Hall.

Hastie, T., Tibshirani, R. (1990) Generalized additive models. 2 ed. Chapman and Hall.

Cook, R. D., Weisberg, S. (1982) Residuals and Influence in Regression. Chapman and Hall.

Atkinson, A.C. (1985) Plots, Transformations and Regression. Oxford University Press.

Pierce, D. A., Schafer, D. W. (1986) Residuals in generalized linear models. Journal of the American Statistical Association, 81(396),977–986.

See Also

fit_core,get_residuals

Examples

data(admrio)
setup(admrio,"date")
f <- resp5~s(time)+weekdays+s(tmpmax)+s(humid)
m <- fit_core(f)
plot_envelope(m)

wjunger/ares documentation built on Dec. 23, 2021, 5:17 p.m.