plot.bivden {sparr} | R Documentation |
Plotting sparr objects
Description
plot
methods for classes bivden
, stden
,
rrs
, rrst
and msden
.
Usage
## S3 method for class 'bivden'
plot(
x,
what = c("z", "edge", "bw"),
add.pts = FALSE,
auto.axes = TRUE,
override.par = TRUE,
...
)
## S3 method for class 'msden'
plot(x, what = c("z", "edge", "bw"), sleep = 0.2, override.par = TRUE, ...)
## S3 method for class 'rrs'
plot(
x,
auto.axes = TRUE,
tol.show = TRUE,
tol.type = c("upper", "lower", "two.sided"),
tol.args = list(levels = 0.05, lty = 1, drawlabels = TRUE),
...
)
## S3 method for class 'rrst'
plot(
x,
tselect = NULL,
type = c("joint", "conditional"),
fix.range = FALSE,
tol.show = TRUE,
tol.type = c("upper", "lower", "two.sided"),
tol.args = list(levels = 0.05, lty = 1, drawlabels = TRUE),
sleep = 0.2,
override.par = TRUE,
expscale = FALSE,
...
)
## S3 method for class 'stden'
plot(
x,
tselect = NULL,
type = c("joint", "conditional"),
fix.range = FALSE,
sleep = 0.2,
override.par = TRUE,
...
)
Arguments
x |
|
what |
A character string to select plotting of result ( |
add.pts |
Logical value indicating whether to add the observations to
the image plot using default |
auto.axes |
Logical value indicating whether to display the plot with automatically added x-y axes and an ‘L’ box in default styles. |
override.par |
Logical value indicating whether to override the
existing graphics device parameters prior to plotting, resetting
|
... |
Additional graphical parameters to be passed to
|
sleep |
Single positive numeric value giving the amount of time (in
seconds) to |
tol.show |
Logical value indicating whether to show pre-computed tolerance contours on the plot(s). The object |
tol.type |
A character string used to control the type of tolerance contour displayed; a test for elevated risk ( |
tol.args |
A named list of valid arguments to be passed directly to |
tselect |
Either a single numeric value giving the time at which to return the plot, or a vector of length 2 giving an interval of times over which to plot. This argument must respect the stored temporal bound in |
type |
A character string to select plotting of joint/unconditional spatiotemporal estimate (default) or conditional spatial density given time. |
fix.range |
Logical value indicating whether use the same color scale limits for each plot in the sequence. Ignored if the user supplies a pre-defined |
expscale |
Logical value indicating whether to force a raw-risk scale. Useful for users wishing to plot a log-relative risk surface, but to have the raw-risk displayed on the colour ribbon. |
Details
In all instances, visualisation is deferred to
plot.im
, for which there are a variety of
customisations available the user can access via ...
. The one
exception is when plotting observation-specific "diggle"
edge
correction factors—in this instance, a plot of the spatial observations is
returned with size proportional to the influence of each correction weight.
When plotting a rrs
object, a pre-computed p-value
surface (see argument tolerate
in risk
) will
automatically be superimposed at a significance level of 0.05. Greater
flexibility in visualisation is gained by using tolerance
in
conjunction with contour
.
An msden
, stden
, or rrst
object is plotted as an animation, one pixel image
after another, separated by sleep
seconds. If instead you intend the
individual images to be plotted in an array of images, you should first set
up your plot device layout, and ensure override.par = FALSE
so that
the function does not reset these device parameters itself. In such an
instance, one might also want to set sleep = 0
.
Value
Plots to the relevant graphics device.
Author(s)
T.M. Davies
Examples
data(pbc)
data(fmd)
data(burk)
# 'bivden' object
pbcden <- bivariate.density(split(pbc)$case,h0=3,hp=2,adapt=TRUE,davies.baddeley=0.05,verbose=FALSE)
plot(pbcden)
plot(pbcden,what="bw",main="PBC cases\n variable bandwidth surface",xlab="Easting",ylab="Northing")
# 'stden' object
burkden <- spattemp.density(burk$cases,tres=128) # observation times are stored in marks(burk$cases)
plot(burkden,fix.range=TRUE,sleep=0.1) # animation
plot(burkden,tselect=c(1000,3000),type="conditional") # spatial densities conditional on each time
# 'rrs' object
pbcrr <- risk(pbc,h0=4,hp=3,adapt=TRUE,tolerate=TRUE,davies.baddeley=0.025,edge="diggle")
plot(pbcrr) # default
plot(pbcrr,tol.args=list(levels=c(0.05,0.01),lty=2:1,col="seagreen4"),auto.axes=FALSE)
# 'rrst' object
f <- spattemp.density(fmd$cases,h=6,lambda=8)
g <- bivariate.density(fmd$controls,h0=6)
fmdrr <- spattemp.risk(f,g,tolerate=TRUE)
plot(fmdrr,sleep=0.1,fix.range=TRUE)
plot(fmdrr,type="conditional",sleep=0.1,tol.type="two.sided",
tol.args=list(levels=0.05,drawlabels=FALSE))
# 'msden' object
pbcmult <- multiscale.density(split(pbc)$case,h0=4,h0fac=c(0.25,2.5))
plot(pbcmult) # densities
plot(pbcmult,what="edge") # edge correction surfaces
plot(pbcmult,what="bw") # bandwidth surfaces