Create and display diagnostic plots for an evm object. See plot.evmOpt
for further details on what is being plotted.
# S3 method for evmOpt
ggplot(
data,
mapping,
which = 1:4,
main = rep(NULL, 4),
xlab = rep(NULL, 4),
nsim = 1000,
alpha = 0.05,
jitter.width = 0,
jitter.height = 0,
ptcol = "blue",
span = 2/3,
col = "light blue",
fill = "orange",
plot. = TRUE,
ncol = 2,
nrow = 2,
...,
environment
)An object of class evm.
ignored
Which plots to produce. Defaults to which=1:4.
Main titles. Should have length 4.
Labels for x-axes.
Number of simulated datasets to create to form tolerance regions.
Used to compute coverage of pointwise confidence intervals.
Used to control the amount of
jittering of points in the plots of the residuals versus
covariates (when covariates are in the model). Defaults to
jitter.width=0, jitter.height = 0.
Colour for points. Defaults to ptcol="blue".
Passed to the loess smoother and defaults to
span=2/3. Sometimes this choice is poor: if the loess
smoother looks wrong, try span=1.
Colour for lines. Defaults to col="light blue".
Colour for confidence regions. Defaults to
fill="orange"
Whether or not to display the output. Defaults to
plot.=TRUE. If the display doesn't have the desired row
and column layout, the user should specify plot.=FALSE,
asign the output to an object, and use grid.arrange to
display it.
The number of columns wanted in the resulting
plot. Defaults to ncol=2. This argument is passed into
grid.arrange.
The number of rows wanted in the resulting
plot. Defaults to nrow=2. This argument is passed into
grid.arrange.
Other arguments passed through to underlying plot functions.
The function attempts to arrange the plots nicely. If the
output isn't what was wanted, the function returns the graphs
to the user as a list so that the user can use
grid.arrange directly. Also, if you have one or more
covariates in the model and the loess smoother looks wrong, try
setting span=1.
plot.evmOpt