plot.fads {ads} | R Documentation |
Plot second-order neighbourhood functions
Description
Plot second-order neighbourhood function estimates returned by functions kfun, k12fun, kmfun
,
kijfun or ki.fun
.
Usage
## S3 method for class 'fads'
plot(x, opt, cols, lty, main, sub, legend, csize, ...)
Arguments
x |
an object of class |
opt |
one of |
cols |
(optional) colours used for plotting functions. |
lty |
(optional) line types used for plotting functions. |
main |
by default, the value of argument x, otherwise a text to be displayed as a title of the plot. |
sub |
by default, the name of the function displayed, otherwise a text to be displayed as function subtitle. |
legend |
If |
csize |
scaling factor for font size so that actual font size is |
... |
extra arguments that will be passed to the plotting functions |
Details
Function plot.fads
displays second-order neighbourhood function estimates as a function of interpoint distance, with expected values
as well as confidence interval limits when computed. Argument x
can be any fads
object returned by functions kfun,
k12fun, kmfun, kijfun or ki.fun
.
Value
none.
Author(s)
See Also
kfun
,
k12fun
,
kmfun
,
kijfun
,
ki.fun
.
Examples
data(BPoirier)
BP <- BPoirier
## Not run: Ripley's function
swr <- spp(BP$trees, win=BP$rect)
k.swr <- kfun(swr, 25, 1, 500)
plot(k.swr)
## Not run: Intertype function
swrm <- spp(BP$trees, win=BP$rect, marks=BP$species)
k12.swrm <- k12fun(swrm, 25, 1, 500, marks=c("beech","oak"))
plot(k12.swrm, opt="L", cols=1)
## Not run: Mark correlation function
swrm <- spp(BP$trees, win=BP$rect, marks=BP$dbh)
km.swrm <- kmfun(swrm, 25, 1, 500)
plot(km.swrm, main="Example 1", sub=NULL, legend=FALSE)