Takes a expectreg object and plots the estimated effects.
# S3 method for expectreg
plot(x, rug = TRUE, xlab = NULL, ylab = NULL, ylim = NULL,
legend = TRUE, ci = FALSE, ask = NULL, cex.main = 2, mar.min = 5, main = NULL,
cols = "rainbow", hcl.par = list(h = c(260, 0), c = 185, l = c(30, 85)),
ylim_spat = NULL, ylim_factor = NULL, range_warning = TRUE, add_intercept = TRUE, ...)No return value, only graphical output.
An object of class expectreg as returned e.g. by the function expectreg.ls.
Boolean. Whether nonlinear effects are displayed in a rug plot.
Graphic parameters. xlab should match the number of covariates.
Boolean. Decides whether a legend is added to the plots.
Boolean. Whether confidence intervals and significances should be plotted.
Should always be asked before a new plot is printed.
Font size of main
Minimal margins, important when markov fields are plotted
Vector of main per plot
Colours sheme of plots. Default is rainbow. Alternatively hcl can be used.
Parameters to specify the hcl coulour sheme.
y_limits of the markov random field and all other spatial methods.
y_limits of the plots of factor covariates.
Should a warning be printed in the graphic if the range of the markov random field/factor plot is larger than the specified limits in markov_ylim/factors_ylim.
Should the intercept be added to the plots of splines?
Graphical parameters passesd on to the standard plot function.
Fabian Otto- Sobotka
Carl von Ossietzky University Oldenburg
https://uol.de
Elmar Spiegel
Georg August University Goettingen
https://www.uni-goettingen.de
The plot function gives a visual representation of the fitted expectiles
separately for each covariate.
Schnabel S and Eilers P (2009) Optimal expectile smoothing Computational Statistics and Data Analysis, 53:4168-4177
Sobotka F and Kneib T (2010) Geoadditive Expectile Regression Computational Statistics and Data Analysis, doi: 10.1016/j.csda.2010.11.015.
expectreg.ls, expectreg.boost, expectreg.qp
data(dutchboys)
expreg <- expectreg.ls(hgt ~ rb(age,"pspline"),data=dutchboys,smooth="f",
expectiles=c(0.05,0.2,0.8,0.95))
plot(expreg)
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