allstats
Calculate four standard summary functions of a point pattern.
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
).
- Keywords
- spatial
Usage
allstats(pp, dataname=NULL, verb=FALSE)
Arguments
- pp
- The observed point pattern, for which summary function
estimates are required. An object of class
"ppp"
. It must not be marked. - dataname
- A character string giving an optional (alternative) name for the point pattern.
- verb
- A logical value meaning ``verbose''. If
TRUE
, progress reports are printed during calculation.
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 function array (an object of class
"fasp"
, seefasp.object
). This can be plotted usingplot.fasp
.The function array has dimensions $2 \times 2$ with the entries at positions
[1,1]
,[1,2]
,[2,1]
and[2,2]
representing $F(r)$, $G(r)$, $J(r)$ and $K(r)$ respectively. Each function entryfns[[i]]
retains the format of the output of the relevant estimating routineFest
,Gest
,Jest
orKest
.The default formulae for plotting these functions are
cbind(km,theo) ~ r
for F, G, and J, andcbind(trans,theo) ~ r
for K.
See Also
Examples
data(swedishpines)
a <- allstats(swedishpines,dataname="Swedish Pines")
plot(a)
plot(a, subset=list("r<=15","r<=15","r<=15","r<=50"))