Tstat.pp3: Extends Tstat to pp3
In aproudian2/rapt: Atom Probe Tomography Analysis

Tstat.pp3

R Documentation

Extends Tstat to pp3

Description

Tstat.pp3 extends the third-order summary statistic Tstat to pp3

Usage

Tstat.pp3(
  X,
  rmax = NULL,
  nrval = 128,
  correction = "border",
  ratio = FALSE,
  verbose = TRUE
)

Arguments

`X`	The observed point pattern, from which an estimate of T(r) will be computed. A `pp3` object.
`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 `nrval` is required to avoid discretisation effects.
`correction`	One of `"none"` or `"isotropic"`. `"translation"` correction is planned but not yet implemented.
`ratio`	Logical. If `TRUE`, the numerator and denominator of each edge-corrected estimate will also be saved, for use in analysing replicated point patterns.
`verbose`	Logical. If `TRUE`, an estimate of the computation time is printed.

Details

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.

Value

An object of class "fv", see fv.object, which can be plotted directly using plot.fv.

References

Schladitz, K. & Baddeley, A. "A third order point process characteristic", Scandinavian Journal of Statistics, 27, 657-671 (2000).

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()