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\name{plot.lm}\alias{plot.lm}\alias{plot.mlm}%which is .NotYetImplemented()\title{Plot Diagnostics for an lm Object}\usage{plot.lm(x, which = 1:4,caption = c("Residuals vs Fitted", "Normal Q-Q plot","Scale-Location plot", "Cook's distance plot"),panel = points,sub.caption = deparse(x$call), main = "",ask = interactive() && one.fig && length(which) > 1&& .Device != "postscript",\dots,id.n = 3, labels.id = names(residuals(x)), cex.id = 0.25)}\arguments{\item{x}{\code{lm} object, typically result of \code{\link{lm}} or\code{\link{glm}}.}\item{which}{If a subset of the plots is required, specify a subset ofthe numbers \code{1:4}.}\item{caption}{Captions to appear above the plots}\item{panel}{Panel function. A useful alternative to\code{\link{points}} is \code{\link{panel.smooth}}.}\item{sub.caption}{common title---above figures if there are multiple;used as \code{sub} (s.\code{\link{title}}) otherwise.}\item{main}{title to each plot---in addition to the above\code{caption}.}\item{ask}{logical; if \code{TRUE}, the user is \emph{ask}ed beforeeach plot, see \code{\link{par}(ask=.)}.}\item{\dots}{other parameters to be passed through to plottingfunctions.}\item{id.n}{number of points to be labelled in each plot, startingwith the most extreme.}\item{labels.id}{vector of labels, from which the labels for extremepoints will be chosen. \code{NULL} uses observation numbers.}\item{cex.id}{magnification of point labels.}}\description{Four plots (choosable by \code{which}) are currently provided: a plotof residuals against fitted values, a Scale-Location plot of\eqn{\sqrt{| residuals |}} against fitted values, a Normal Q-Q plot,and a plot of Cook's distances versus row labels.}\details{\code{sub.caption}---by default the function call---is shown asa subtitle (under the x-axis title) on each plot when plots are onseparate pages, or as a subtitle in the outer margin (if any) whenthere are multiple plots per page.The ``Scale-Location'' plot, also called ``Spread-Location'' or``S-L'' plot, takes the square root of the absolute residuals inorder to diminish skewness (\eqn{\sqrt{| E |}} is much less skewedthan \eqn{| E |} for Gaussian zero-mean \eqn{E}).This `S-L' and the Q-Q plot use \emph{standardized} residuals whichhave identical variance (under the hypothesis). They are given as\eqn{R_i / (s \times \sqrt{1 - h_{ii}})}{R[i] / (s*sqrt(1 - h.ii))}where \eqn{h_{ii}}{h.ii} are the diagonal entries of the hat matrix,% bug in Rdconv: "$" and \link inside \code fails; '\$' doesn't help :\code{\link{lm.influence}()}\code{$hat}, see also \code{\link{hat}}.}\references{Belsley, D. A., Kuh, E. and Welsch, R. E. (1980)\emph{Regression Diagnostics.} New York: Wiley.Cook, R. D. and Weisberg, S. (1982)\emph{Residuals and Influence in Regression.}London: Chapman and Hall.Hinkley, D. V. (1975) On power transformations tosymmetry. \emph{Biometrika} \bold{62}, 101--111.McCullagh, P. and Nelder, J. A. (1989)\emph{Generalized Linear Models.}London: Chapman and Hall.}\author{John Maindonald and Martin Maechler.}\seealso{\code{\link{termplot}}, \code{\link{lm.influence}},\code{\link{cooks.distance}}.}\examples{## Analysis of the life-cycle savings data## given in Belsley, Kuh and Welsch.data(LifeCycleSavings)plot(lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings))## 4 plots on 1 page; allow room for printing model formula in outer margin:par(mfrow = c(2, 2), oma = c(0, 0, 2, 0))plot(lm.SR)plot(lm.SR, id.n = NULL) # no id'splot(lm.SR, id.n = 5, labels.id = NULL)# 5 id numbers## Fit a smmooth curve, where applicable:plot(lm.SR, panel = panel.smooth)## Gives a smoother curveplot(lm.SR, panel = function(x,y) panel.smooth(x, y, span = 1))par(mfrow=c(2,1))# same oma as aboveplot(lm.SR, which = 1:2, sub.caption = "Saving Rates, n=50, p=5")\testonly{% which=4 failed in R 1.0.1par(mfrow=c(1,1), oma= rep(0,4))data(longley)summary(lm.fm2 <- lm(Employed ~ . - Population - GNP.deflator, data = longley))for(wh in 1:4) plot(lm.fm2, which = wh)}}\keyword{hplot}\keyword{regression}