plot.boxcoxLm: Plot Results of Box-Cox Transformations for a Linear Model

Description

Plot the results of calling the function boxcox when the argument x supplied to boxcox is an object of class "lm". Three different kinds of plots are available. The function plot.boxcoxLm is automatically called by plot when given an object of class "boxcoxLm". The names of other functions associated with Box-Cox transformations are listed under Data Transformations.

Usage

## S3 method for class 'boxcoxLm':
plot(x, plot.type = "Objective vs. lambda", same.window = TRUE, 
    ask = same.window & plot.type != "Ojective vs. lambda", 
    plot.pos.con = 0.375, estimate.params = FALSE, 
    equal.axes = qq.line.type == "0-1" || estimate.params, add.line = TRUE, 
    qq.line.type = "least squares", duplicate.points.method = "standard", 
    points.col = 1, line.col = 1, line.lwd = par("cex"), line.lty = 1, 
    digits = .Options$digits, cex.main = 1.4 * par("cex"), cex.sub = par("cex"), 
    main = NULL, sub = NULL, xlab = NULL, ylab = NULL, xlim = NULL, 
    ylim = NULL, ...)

Arguments

an object of class "boxcoxLm". See boxcoxLm.object for details.

plot.type

character string indicating what kind of plot to create. Only one particular plot type will be created, unless plot.type="All", in which case all plots will be created sequentially. The possible values of plot.type are:

same.window

logical scalar indicating whether to produce all plots in the same graphics window (same.window=TRUE; the default), or to create a new graphics window for each separate plot (same.window=FALSE). The argument is relev

ask

logical scalar supplied to the function devAskNewPage, indicating whether to prompt the user before creating a new plot within a single graphics window. This argument is ignored when pl

points.col

numeric scalar determining the color of the points in the plot. The default value is points.col=1. See the entry for col in the Rhelp file for par for more information.

plot.pos.con

numeric scalar between 0 and 1 containing the value of the plotting position constant used to construct the Q-Q plots and/or Tukey Mean-Difference Q-Q plots. The default value is plot.pos.con=0.375. See the help files for

estimate.params

logical scalar indicating whether to compute quantiles based on estimating the distribution parameters (estimate.params=TRUE) or using the distribution parameters for a standard normal distribution (i.e, mean=0,

equal.axes

logical scalar indicating whether to use the same range on the $x$- and $y$-axes when plot.type="Q-Q Plots". The default value is TRUE if qq.line.type="0-1" or estimate.params=TRUE, otherwis

add.line

logical scalar indicating whether to add a line to the plot. If add.line=TRUE and plot.type="Q-Q Plots", a line determined by the value of qq.line.type is added to the plot. If add.line=TRUE an

qq.line.type

character string determining what kind of line to add to the plot when plot.type="Q-Q Plots". Possible values are "least squares" (a least squares line; the default), "0-1" (a line with intercept 0 and s

duplicate.points.method

a character string denoting how to plot points with duplicate $(x,y)$ values. Possible values are "standard" (a single plotting symbol is plotted; the default), "jitter" (a separate plotting symbol is plotted for eac

line.col

numeric scalar determining the color of the line in the plot. The default value is line.col=1. See the entry for col in the Rhelp file for par for more information. This arg

line.lwd

numeric scalar determining the width of the line in the plot. The default value is line.lwd=par("cex"). See the entry for lwd in the Rhelp file for par for more information.

line.lty

numeric scalar determining the line type (style) of the line in the plot. The default value is line.lty=1. See the entry for lty in the Rhelp file for par for more informatio

digits

scalar indicating how many significant digits to print for the distribution parameters and the value of the objective in the sub-title. The default value is the current setting of options("digits").

cex.main, cex.sub, main, sub, xlab, ylab, xlim, ylim, ...

graphics parameters; see par for more information. The default value of cex.main is cex.main=1.4 * par("cex"). The default value of cex.sub is cex.sub=par(

Value

plot.boxcoxLm invisibly returns the first argument, x.

Details

The function plot.boxcoxLm is a method for the generic function plot for the class "boxcoxLm" (see boxcoxLm.object). It can be invoked by calling plot and giving it an object of class "boxcoxLm" as the first argument, or by calling plot.boxcoxLm directly, regardless of the class of the object given as the first argument to plot.boxcoxLm. Plots associated with Box-Cox transformations are produced on the current graphics device. These can be one or all of the following:

Objective vs.$\lambda$.
Observed Quantiles vs. Normal Quantiles (Q-Q Plot) for the residuals of the linear model based on transformed values of the response variable for each of the values of$\lambda$.
Tukey Mean-Difference Q-Q Plots for the residuals of the linear model based on transformed values of the response variable for each of the values of$\lambda$.

See the help files for boxcox and qqPlot for more information.

References

Chambers, J. M. and Hastie, T. J. (1992). Statistical Models in S. Wadsworth & Brooks/Cole.

Examples

Run this code

# Create an object of class "boxcoxLm", then plot the results.

  # The data frame Environmental.df contains daily measurements of 
  # ozone concentration, wind speed, temperature, and solar radiation
  # in New York City for 153 consecutive days between May 1 and 
  # September 30, 1973.  In this example, we'll model ozone as a 
  # function of temperature.

  # Fit the model with the raw Ozone data
  #--------------------------------------
  ozone.fit <- lm(ozone ~ temperature, data = Environmental.df) 

  boxcox.list <- boxcox(ozone.fit)

  # Plot PPCC vs. lambda based on Q-Q plots of residuals 
  #-----------------------------------------------------
  dev.new()
  plot(boxcox.list) 

  # Look at Q-Q plots of residuals for the various transformation 
  #--------------------------------------------------------------
  plot(boxcox.list, plot.type = "Q-Q Plots", same.window = FALSE)


  # Look at Tukey Mean-Difference Q-Q plots of residuals 
  # for the various transformation 
  #-----------------------------------------------------
  plot(boxcox.list, plot.type = "Tukey M-D Q-Q Plots", same.window = FALSE)

  #==========

  # Clean up
  #---------
  rm(ozone.fit, boxcox.list)
  graphics.off()

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