Plot Results of Group Goodness-of-Fit Test
Plot the results of calling the function gofGroupTest
,
which returns an object of class "gofGroup"
when performing a
goodness-of-fit test to determine whether data in a set of
groups appear to all come from the same probability distribution
(with possibly different parameters for each group).
Five different kinds of plots are available.
The function plot.gofGroup
is automatically called by plot
when given an object of class "gofGroup"
. The names of other functions
associated with goodness-of-fit test are listed under Goodness-of-Fit Tests.
## S3 method for class 'gofGroup' plot(x, plot.type = "Summary", captions = list(QQ = NULL, MDQQ = NULL, ScoresQQ = NULL, ScoresMDQQ = NULL, Results = NULL), x.labels = list(QQ = NULL, MDQQ = NULL, ScoresQQ = NULL, ScoresMDQQ = NULL), y.labels = list(QQ = NULL, MDQQ = NULL, ScoresQQ = NULL, ScoresMDQQ = NULL), same.window = FALSE, ask = same.window & plot.type == "All", add.line = TRUE, digits = ifelse(plot.type == "Summary", 2, .Options$digits), test.result.font = 1, test.result.cex = ifelse(plot.type == "Summary", 0.9, 1) * par("cex"), test.result.mar = c(0, 0, 3, 0) + 0.1, individual.p.values = FALSE, cex.main = ifelse(plot.type == "Summary", 1.2, 1.5) * par("cex"), cex.axis = ifelse(plot.type == "Summary", 0.9, 1) * par("cex"), cex.lab = ifelse(plot.type == "Summary", 0.9, 1) * par("cex"), main = NULL, xlab = NULL, ylab = NULL, xlim = NULL, ylim = NULL, add.om.title = TRUE, oma = if (plot.type == "Summary" & add.om.title) c(0, 0, 5, 0) else c(0, 0, 0, 0), om.title = NULL, om.font = 2, om.cex.main = 1.5 * par("cex"), om.line = 1, ...)
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 |
captions |
a list with 1 to 5 components with the names |
x.labels |
a list of 1 to 4 components with the names |
y.labels |
a list of 1 to 4 components with the names |
same.window |
logical scalar indicating whether to produce all plots in the same graphics
window ( |
ask |
logical scalar supplied to the function |
add.line |
logical scalar indicating whether to add a line to the plot. If |
Arguments associated with plot.type="Test Results"
digits |
scalar indicating how many significant digits to print for the test results
when |
individual.p.values |
logical scalar indicating whether to display the p-values associated with
each individual group. The default value is |
test.result.font |
numeric scalar indicating which font to use to print out the test results.
The default value is |
test.result.cex |
numeric scalar indicating the value of |
test.result.mar |
numeric vector indicating the value of |
Arguments associated with plot.type="Summary"
add.om.title |
logical scalar indicating whether to add a title in the outer margin when |
om.title |
character string containing the outer margin title. The default value is |
om.font |
numeric scalar indicating the font to use for the outer margin. The default
value is |
om.cex.main |
numeric scalar indicating the value of |
om.line |
numeric scalar indicating the line to place the outer margin title on. The
default value is |
Graphics parameters:
cex.main, cex.axis, cex.lab, main, xlab, ylab, xlim, ylim, oma, ... |
additional graphics parameters. See the help file for |
The function plot.gofGroup
is a method for the generic function
plot
for the class "gofGroup"
(see
gofGroup.object
).
It can be invoked by calling plot
and giving it an object of
class "gofGroup"
as the first argument, or by calling
plot.gofGroup
directly, regardless of the class of the object given
as the first argument to plot.gofGroup
.
Plots associated with the goodness-of-fit test are produced on the current graphics device. These can be one or all of the following:
plot.type="Q-Q Plot"
.
Q-Q Plot of observed p-values vs. quantiles from a
Uniform [0,1] distribution.
See the help file for qqPlot
.
plot.type="Tukey M-D Q-Q Plot"
.
Tukey mean-difference Q-Q plot for observed p-values and
quantiles from a Uniform [0,1] distribution.
See the help file for qqPlot
.
plot.type="Scores Q-Q Plot"
.
Q-Q Plot of Normal scores vs. quantiles from a
Normal(0,1) distribution or
Q-Q Plot of Chisquare scores vs. quantiles from a
Chisquare distribution with 2 degrees of freedom.
See the help file for qqPlot
.
plot.type="Scores Tukey M-D Q-Q Plot"
.
Tukey mean-difference Q-Q plot based on Normal scores or
Chisquare scores.
See the help file for qqPlot
.
Results of the goodness-of-fit test (plot.type="Test Results"
).
See the help file for print.gofGroup
.
See the help file for gofGroupTest
for more information.
plot.gofGroup
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.
# Create an object of class "gofGroup" then plot it. # Example 10-4 of USEPA (2009, page 10-20) gives an example of # simultaneously testing the assumption of normality for nickel # concentrations (ppb) in groundwater collected at 4 monitoring # wells over 5 months. The data for this example are stored in # EPA.09.Ex.10.1.nickel.df. EPA.09.Ex.10.1.nickel.df # Month Well Nickel.ppb #1 1 Well.1 58.8 #2 3 Well.1 1.0 #3 6 Well.1 262.0 #... #18 6 Well.4 85.6 #19 8 Well.4 10.0 #20 10 Well.4 637.0 # Test for a normal distribution at each well: #-------------------------------------------- gofGroup.obj <- gofGroupTest(Nickel.ppb ~ Well, data = EPA.09.Ex.10.1.nickel.df) dev.new() plot(gofGroup.obj) # Make your own titles for the summary plot #------------------------------------------ dev.new() plot(gofGroup.obj, captions = list(QQ = "Q-Q Plot", ScoresQQ = "Scores Q-Q Plot", Results = "Results"), om.title = "Summary Plot") # Just the Q-Q Plot #------------------ dev.new() plot(gofGroup.obj, plot.type="Q-Q") # Make your own title for the Q-Q Plot #------------------------------------- dev.new() plot(gofGroup.obj, plot.type="Q-Q", main = "Q-Q Plot") #========== # Clean up #--------- rm(gofGroup.obj) graphics.off()
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.