Plot Results of Box-Cox Transformations Based on Type I Censored Data
Plot the results of calling the function boxcoxCensored,
which returns an object of class "boxcoxCensored". Three different kinds of plots are available.
The function plot.boxcoxCensored is automatically called by plot
when given an object of class "boxcoxCensored".
## S3 method for class 'boxcoxCensored'
plot(x, plot.type = "Objective vs. lambda", same.window = TRUE,
ask = same.window & plot.type != "Ojective vs. lambda",
prob.method = "michael-schucany", 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, ...)x |
an object of class |
plot.type |
character string indicating what kind of plot to create. Only one particular
plot type will be created, unless |
same.window |
logical scalar indicating whether to produce all plots in the same graphics
window ( |
ask |
logical scalar supplied to the function |
points.col |
numeric scalar determining the color of the points in the plot. The default
value is |
The following arguments can be supplied when plot.type="Q-Q Plots", plot.type="Tukey M-D Q-Q Plots", or plot.type="All"
(supplied to qqPlot):
prob.method |
character string indicating what method to use to compute the plotting positions
for Q-Q plots or Tukey Mean-Difference Q-Q plots.
Possible values are
The This argument is ignored if |
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 |
estimate.params |
logical scalar indicating whether to compute quantiles based on estimating the
distribution parameters ( |
equal.axes |
logical scalar indicating whether to use the same range on the x- and
y-axes when |
add.line |
logical scalar indicating whether to add a line to the plot. If |
qq.line.type |
character string determining what kind of line to add to the plot when |
duplicate.points.method |
a character string denoting how to plot points with duplicate (x,y) values.
Possible values are |
line.col |
numeric scalar determining the color of the line in the plot. The default value
is |
line.lwd |
numeric scalar determining the width of the line in the plot. The default value
is |
line.lty |
numeric scalar determining the line type (style) of the line in the plot.
The default value is |
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 |
Graphics parameters:
cex.main, cex.sub, main, sub, xlab, ylab, xlim, ylim, ... |
graphics parameters; see |
The function plot.boxcoxCensored is a method for the generic function
plot for the class "boxcoxCensored" (see boxcoxCensored.object).
It can be invoked by calling plot and giving it an object of
class "boxcoxCensored" as the first argument, or by calling
plot.boxcoxCensored directly, regardless of the class of the object given
as the first argument to plot.boxcoxCensored.
Plots associated with Box-Cox transformations are produced on the current graphics device. These can be one or all of the following:
Objective vs. λ.
Observed Quantiles vs. Normal Quantiles (Q-Q Plot) for the transformed observations for each of the values of λ.
Tukey Mean-Difference Q-Q Plots for the transformed observations for each of the values of λ.
See the help files for boxcoxCensored and qqPlotCensored
for more information.
plot.boxcoxCensored invisibly returns the first argument, x.
Steven P. Millard (EnvStats@ProbStatInfo.com)
Chambers, J. M. and Hastie, T. J. (1992). Statistical Models in S. Wadsworth & Brooks/Cole.
# Generate 15 observations from a lognormal distribution with # mean=10 and cv=2 and censor the observations less than 2. # Then generate 15 more observations from this distribution and # censor the observations less than 4. # Then call the function boxcoxCensored, and then plot the results. # (Note: the call to set.seed simply allows you to reproduce this example.) set.seed(250) x.1 <- rlnormAlt(15, mean = 10, cv = 2) censored.1 <- x.1 < 2 x.1[censored.1] <- 2 x.2 <- rlnormAlt(15, mean = 10, cv = 2) censored.2 <- x.2 < 4 x.2[censored.2] <- 4 x <- c(x.1, x.2) censored <- c(censored.1, censored.2) # Plot the results based on the PPCC objective #--------------------------------------------- boxcox.list <- boxcoxCensored(x, censored) dev.new() plot(boxcox.list) # Look at Q-Q Plots for the candidate values of lambda #----------------------------------------------------- plot(boxcox.list, plot.type = "Q-Q Plots", same.window = FALSE) # Look at Tukey Mean-Difference Q-Q Plots # for the candidate values of lambda #---------------------------------------- plot(boxcox.list, plot.type = "Tukey M-D Q-Q Plots", same.window = FALSE) #========== # Clean up #--------- rm(x.1, censored.1, x.2, censored.2, x, censored, boxcox.list) graphics.off()
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