Tstat.pp3 | R Documentation |
Tstat.pp3 extends the third-order summary statistic
Tstat
to pp3
Tstat.pp3( X, rmax = NULL, nrval = 128, correction = "border", ratio = FALSE, verbose = TRUE )
X |
The observed point pattern, from which an estimate of T(r)
will be computed. A |
rmax |
Optional. Maximum value of argument r for which T(r) will be estimated. |
nrval |
Optional. Number of values of r for which
T(r) will be estimated. A large value of |
correction |
One of |
ratio |
Logical. If |
verbose |
Logical. If |
This command calculates the third-order summary statistic T(r) for a spatial point patterns, defined by Schladitz and Baddeley (2000).
The definition of T(r) is similar to the definition of Ripley's K function K(r), except that K(r) counts pairs of points while T(r) counts triples of points. Essentially T(r) is a rescaled cumulative distribution function of the diameters of triangles in the point pattern. The diameter of a triangle is the length of its longest side.
An object of class "fv
", see fv.object
,
which can be plotted directly using plot.fv
.
Schladitz, K. & Baddeley, A. "A third order point process characteristic", Scandinavian Journal of Statistics, 27, 657-671 (2000).
Tstat
Other spatstat extensions:
G3cross()
,
G3multi()
,
K3scaled()
,
bdist.points()
,
marktable.pp3()
,
marktable()
,
quadratcount.pp3()
,
quadrats.pp3()
,
rPoissonCluster3()
,
rjitter.pp3()
,
rjitter.ppp()
,
rjitter()
,
rpoint3()
,
sample.pp3()
,
sample.ppp()
,
shift.pp3()
,
studpermu.test.pp3()
,
studpermu.test()
,
superimpose.pp3()
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