sfsmisc: TA.plot – R documentation

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TA.plot

Tukey-Anscombe Plot (Residual vs. Fitted) of a Linear Model

Description

From a linear (or glm) model fitted, produce the so-called Tukey-Anscombe plot. Useful (optional) additions include: 0-line, lowess smooth, 2sigma lines, and automatic labeling of observations.

Usage

TA.plot(lm.res,
        fit= fitted(lm.res), res= residuals(lm.res, type="pearson"),
        labels= NULL, main= mk.main(), xlab = "Fitted values",
        draw.smooth= n >= 10, show.call = TRUE, show.2sigma= TRUE,
        lo.iter = NULL, lo.cex= NULL,
        par0line  = list(lty = 2, col = "gray"),
        parSmooth = list(lwd = 1.5, lty = 4, col = 2),
        parSigma  = list(lwd = 1.2, lty = 3, col = 4),
        verbose = FALSE,
        ...)

Arguments

`lm.res`	Result of `lm(..)`, `aov(..)`, `glm(..)` or a similar object.
`fit`	fitted values; you probably want the default here.
`res`	residuals to use. Default: Weighted ("Pearson") residuals if weights have been used for the model fit.
`labels`	strings to use as plotting symbols for each point. Default(`NULL`): extract observations' names or use its sequence number. Use, e.g., "" to get simple `` symbols.
`main`	main title to plot. Default: sophisticated, resulting in something like "Tukey-Anscombe Plot of : y \~ x" constructed from `lm.res $ call`.
`xlab`	x-axis label for plot.
`draw.smooth`	logical; if `TRUE`, draw a `lowess` smoother (with automatic smoothing fraction).
`show.call`	logical; if `TRUE`, write the "call"ing syntax with which the fit was done.
`show.2sigma`	logical; if `TRUE`, draw horizontal lines at +- 2 sigma where σ is `mad(resid)`.
`lo.iter`	positive integer, giving the number of lowess robustness iterations. The default depends on the model and is `0` for non Gaussian `glm`'s.
`lo.cex`	character expansion ("cex") for lowess and other marginal texts.
`par0line`	a list of arguments (with reasonable defaults) to be passed to `abline(.)` when drawing the x-axis, i.e., the y = 0 line.
`parSmooth, parSigma`	each a list of arguments (with reasonable default) for drawing the smooth curve (if `draw.smooth` is true), or the horizontal sigma boundaries (if `show.2sigma` is true) respectively.
`verbose`	logical indicating if some construction details should be reported (`print()`ed).
`...`	further graphical parameters are passed to `n.plot(.)`.

Side Effects

The above mentioned plot is produced on the current graphic device.

Author(s)

Martin Maechler, Seminar fuer Statistik, ETH Zurich, Switzerland; maechler@stat.math.ethz.ch

Examples

data(stackloss)
TA.plot(lm(stack.loss ~ stack.x))

example(airquality)
summary(lmO <- lm(Ozone ~ ., data= airquality))
TA.plot(lmO)
TA.plot(lmO, label = "O") # instead of case numbers

if(FALSE) { 
 TA.plot(lm(cost ~ age+type+car.age, claims, weights=number, na.action=na.omit))
}

##--- for  aov(.) : -------------
data(Gun, package = "nlme")
TA.plot( aov(rounds ~ Method + Physique/Team, data = Gun))

##--- Not so clear what it means for GLM, but: ------
if(require(rpart)) { # for the two datasets only
 data(solder, package = "rpart")
 TA.plot(glm(skips ~ ., data = solder, family = poisson), cex= .6)

 data(kyphosis, package = "rpart")
 TA.plot(glm(Kyphosis ~ poly(Age,2) + Start, data=kyphosis, family = binomial),
	 cex=.75) # smaller title and plotting characters
}

sfsmisc

Utilities from 'Seminar fuer Statistik' ETH Zurich

v1.1-11

GPL (>= 2)

Authors

Martin Maechler [aut, cre] (<https://orcid.org/0000-0002-8685-9910>), Werner Stahel [ctb] (Functions: compresid2way(), f.robftest(), last(), p.scales(), p.dnorm()), Andreas Ruckstuhl [ctb] (Functions: p.arrows(), p.profileTraces(), p.res.2x()), Christian Keller [ctb] (Functions: histBxp(), p.tachoPlot()), Kjetil Halvorsen [ctb] (Functions: KSd(), ecdf.ksCI()), Alain Hauser [ctb] (Functions: cairoSwd(), is.whole(), toLatex.numeric()*), Christoph Buser [ctb] (to function Duplicated()), Lorenz Gygax [ctb] (to function p.res.2fact()), Bill Venables [ctb] (Functions: empty.dimnames(), primes()), Tony Plate [ctb] (to inv.seq()), Isabelle Fl<fc>ckiger [ctb], Marcel Wolbers [ctb], Markus Keller [ctb], Sandrine Dudoit [ctb], Jane Fridlyand [ctb], Greg Snow [ctb] (to loessDemo()), Henrik Aa. Nielsen [ctb] (to loessDemo()), Vincent Carey [ctb], Ben Bolker [ctb], Philippe Grosjean [ctb], Fr<e9>d<e9>ric Ibanez [ctb], Caterina Savi [ctb], Charles Geyer [ctb], Jens Oehlschl<e4>gel [ctb]

Initial release

2021-04-03