% File nlme/man/plot.gls.Rd % Part of the nlme package for R % Distributed under GPL 2 or later: see nlme/LICENCE.note \name{plot.gls} \title{Plot a gls Object} \usage{ \method{plot}{gls}(x, form, abline, id, idLabels, idResType, grid, \dots) } \alias{plot.gls} \arguments{ \item{x}{an object inheriting from class \code{"\link{gls}"}, representing a generalized least squares fitted linear model.} \item{form}{an optional formula specifying the desired type of plot. Any variable present in the original data frame used to obtain \code{x} can be referenced. In addition, \code{x} itself can be referenced in the formula using the symbol \code{"."}. Conditional expressions on the right of a \code{|} operator can be used to define separate panels in a Trellis display. Default is \code{resid(., type = "p") ~ fitted(.) }, corresponding to a plot of the standardized residuals versus fitted values, both evaluated at the innermost level of nesting.} \item{abline}{an optional numeric value, or numeric vector of length two. If given as a single value, a horizontal line will be added to the plot at that coordinate; else, if given as a vector, its values are used as the intercept and slope for a line added to the plot. If missing, no lines are added to the plot.} \item{id}{an optional numeric value, or one-sided formula. If given as a value, it is used as a significance level for a two-sided outlier test for the standardized residuals. Observations with absolute standardized residuals greater than the \eqn{1 - value/2} quantile of the standard normal distribution are identified in the plot using \code{idLabels}. If given as a one-sided formula, its right hand side must evaluate to a logical, integer, or character vector which is used to identify observations in the plot. If missing, no observations are identified.} \item{idLabels}{an optional vector, or one-sided formula. If given as a vector, it is converted to character mode and used to label the observations identified according to \code{id}. If given as a one-sided formula, its right hand side must evaluate to a vector which is converted to character mode and used to label the identified observations. Default is the innermost grouping factor.} \item{idResType}{an optional character string specifying the type of residuals to be used in identifying outliers, when \code{id} is a numeric value. If \code{"pearson"}, the standardized residuals (raw residuals divided by the corresponding standard errors) are used; else, if \code{"normalized"}, the normalized residuals (standardized residuals pre-multiplied by the inverse square-root factor of the estimated error correlation matrix) are used. Partial matching of arguments is used, so only the first character needs to be provided. Defaults to \code{"pearson"}.} \item{grid}{an optional logical value indicating whether a grid should be added to plot. Default depends on the type of Trellis plot used: if \code{xyplot} defaults to \code{TRUE}, else defaults to \code{FALSE}.} \item{\dots}{optional arguments passed to the Trellis plot function.} } \description{ Diagnostic plots for the linear model fit are obtained. The \code{form} argument gives considerable flexibility in the type of plot specification. A conditioning expression (on the right side of a \code{|} operator) always implies that different panels are used for each level of the conditioning factor, according to a Trellis display. If \code{form} is a one-sided formula, histograms of the variable on the right hand side of the formula, before a \code{|} operator, are displayed (the Trellis function \code{histogram} is used). If \code{form} is two-sided and both its left and right hand side variables are numeric, scatter plots are displayed (the Trellis function \code{xyplot} is used). Finally, if \code{form} is two-sided and its left had side variable is a factor, box-plots of the right hand side variable by the levels of the left hand side variable are displayed (the Trellis function \code{bwplot} is used). } \value{ a diagnostic Trellis plot. } \author{José Pinheiro and Douglas Bates \email{bates@stat.wisc.edu}} \seealso{\code{\link{gls}}, \code{\link{xyplot}}, \code{\link{bwplot}}, \code{\link{histogram}} } \examples{ fm1 <- gls(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary, correlation = corAR1(form = ~ 1 | Mare)) # standardized residuals versus fitted values by Mare plot(fm1, resid(., type = "p") ~ fitted(.) | Mare, abline = 0) # box-plots of residuals by Mare plot(fm1, Mare ~ resid(.)) # observed versus fitted values by Mare plot(fm1, follicles ~ fitted(.) | Mare, abline = c(0,1)) } \keyword{models}