Computes the third order summary statistic \(T(r)\) of a spatial point pattern.
Tstat(X, ..., r = NULL, rmax = NULL,
correction = c("border", "translate"), ratio = FALSE, verbose=TRUE)The observed point pattern,
from which an estimate of \(T(r)\) will be computed.
An object of class "ppp", or data
in any format acceptable to as.ppp().
Ignored.
Optional. Vector of values for the argument \(r\) at which \(T(r)\) should be evaluated. Users are advised not to specify this argument; there is a sensible default.
Optional. Numeric. The maximum value of \(r\) for which \(T(r)\) should be estimated.
Optional. A character vector containing any selection of the
options "none", "border", "bord.modif",
"translate", "translation", or "best".
It specifies the edge correction(s) to be applied.
Alternatively correction="all" selects all options.
Logical.
If TRUE, the numerator and denominator of
each edge-corrected estimate will also be saved,
for use in analysing replicated point patterns.
Logical. If TRUE, an estimate of the computation time
is printed.
An object of class "fv", see fv.object,
which can be plotted directly using plot.fv.
If the number of points is large, the algorithm can take a very long time
to inspect all possible triangles. A rough estimate
of the total computation time will be printed at the beginning
of the calculation. If this estimate seems very large,
stop the calculation using the user interrupt signal, and
call Tstat again, using rmax to restrict the
range of r values,
thus reducing the number of triangles to be inspected.
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.
Schladitz, K. and Baddeley, A. (2000) A third order point process characteristic. Scandinavian Journal of Statistics 27 (2000) 657--671.
# NOT RUN {
plot(Tstat(redwood))
# }
Run the code above in your browser using DataLab