| allstats {spatstat.explore} | R Documentation |
Calculate four standard summary functions of a point pattern.
Description
Calculates the F, G, J, and K
summary functions for an unmarked point pattern.
Returns them as a function array (of class "fasp", see
fasp.object).
Usage
allstats(pp, ..., dataname=NULL, verb=FALSE)
Arguments
pp |
The observed point pattern, for which summary function
estimates are required. An object of class |
... |
Optional arguments passed to the summary functions
|
dataname |
A character string giving an optional (alternative) name for the point pattern. |
verb |
A logical value meaning “verbose”. If |
Details
This computes four standard summary statistics for a
point pattern: the empty space function F(r),
nearest neighbour distance distribution function G(r),
van Lieshout-Baddeley function J(r)
and Ripley's function K(r).
The real work is done by
Fest, Gest, Jest and
Kest respectively. Consult the help files for these functions
for further information about the statistical interpretation
of F, G, J and K.
If verb is TRUE, then “progress reports”
(just indications of completion) are printed out when the
calculations are finished for each of the four function types.
The overall title of the array of four functions
(for plotting by plot.fasp)
will be formed from the argument dataname.
If this is not given, it defaults to the expression
for pp given in the call to allstats.
Value
A list of length 4 containing the F, G, J and
K functions respectively.
The list can be plotted directly using plot (which dispatches to
plot.anylist).
Each list entry retains the format
of the output of the relevant estimating routine
Fest, Gest, Jest or
Kest. Thus each entry in the list is
a function value table (object of class "fv",
see fv.object).
The default formulae for plotting these functions are
cbind(km,theo) ~ r for F, G, and J, and
cbind(trans,theo) ~ r for K.
Author(s)
Adrian Baddeley Adrian.Baddeley@curtin.edu.au and Rolf Turner rolfturner@posteo.net
See Also
plot.anylist,
plot.fv,
fv.object,
Fest,
Gest,
Jest,
Kest
Examples
a <- allstats(swedishpines,dataname="Swedish Pines")
if(interactive()) {
plot(a)
plot(a, subset=list("r<=15","r<=15","r<=15","r<=50"))
}