diagnostics: Diagnostics

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

Description

Perform a series of model dignostics

Usage

diagnostics(model, single.graph = TRUE)

Arguments

model	a model fitted by fit_core
single.graph	a logical indicating whether all graphs should be plotted on the same device windows

Details

This function is a short-cut to several common diagnostics used when analysing time series of outcomes in environmental epidemiology. The following procedures are executed by diagnostics: plot of fitted values with plot_fitted, plot of residuals with plot_residuals, plot of Cook's distance with plot_cook, plot of partial autocorrelation function with plot_pacf, plot of periodogram with periodogram, quantile-quantile plot with plot_qq, and information on parameters and smooth functions estimates print_summary.

If all the graphs are plotted on the same device window, it can be rather difficult to read, but it is more suitable for publications and the graph can be saved with high quality format using save.plot.

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.

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

Schwartz, J., Spix, C., Touloumi, G. et al. (1996) Methodological issues in studies of air pollution and daily counts of deaths or hospital admissions. J Epidemiol. Community Health 50 (suppl 1), S12–S18.

See Also

fit_core,summary

Examples

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

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