Last data update: 2014.03.03
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R: Forward Search in Generalized Linear Models
plot.fwdglm | R Documentation |
Forward Search in Generalized Linear Models
Description
This function plots the results of a forward search analysis in generalized linear models.
Usage
## S3 method for class 'fwdglm'
plot(x, which.plots = 1:11, squared = FALSE, scaled =FALSE,
ylim = NULL, xlim = NULL, th.Res = 4, th.Lev = 0.25, sig.Tst =2.58,
sig.score = 1.96, plot.pf = FALSE, labels.in.plot = TRUE, ...)
Arguments
x |
a "fwdglm" object.
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which.plots |
select which plots to draw, by default all. Each graph is addressed by an integer:
deviance residuals
leverages
maximum deviance residuals
minimum deviance residuals
coefficients
t statistics, i.e. coef.est/SE(coef.est)
likelihood matrix: deviance, deviance explained, pseudo R-squared, dispersion parameter
score statistic for the goodness of link test
forward Cook's distances
modified forward Cook's distances
weights used at each step of the forward search for the units included
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squared |
logical, if TRUE plots squared deviance residuals.
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scaled |
logical, if TRUE plots scaled coefficient estimates.
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ylim |
a two component vector for the min and max of the y axis.
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xlim |
a two component vector for the min and max of the x axis.
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th.Res |
numerical, a threshold for labelling the residuals.
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th.Lev |
numerical, a threshold for labelling the leverages.
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sig.Tst |
numerical, a value used to draw the confidence interval on the plot of the t statistics.
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sig.score |
numerical, a value used to draw the confidence interval on the plot of the score test statistic.
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plot.pf |
logical, in case of binary response if TRUE graphs contain all the step of the forward search, otherwise only those in which there is no perfect fit.
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labels.in.plot |
logical, if TRUE units are labelled in the plots when required.
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... |
further arguments passed to or from other methods.
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Author(s)
Originally written for S-Plus by:
Kjell Konis kkonis@insightful.com and Marco Riani mriani@unipr.it
Ported to R by Luca Scrucca luca@stat.unipg.it
References
Atkinson, A.C. and Riani, M. (2000), Robust Diagnostic Regression Analysis, First Edition. New York: Springer, Chapter 6.
See Also
fwdglm , fwdlm , fwdsco .
Examples
## Not run: data(cellular)
## Not run: mod <- fwdglm(y ~ as.factor(TNF) + as.factor(IFN), data=cellular,
family=poisson(log), nsamp=200)
## End(Not run)
## Not run: summary(mod)
## Not run: plot(mod)
Results
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