Perform a studentised permutation test for a difference between groups of point patterns.
studpermu.test(X, formula, summaryfunction = Kest,
…, rinterval = NULL, nperm = 999,
use.Tbar = FALSE, minpoints = 20, rsteps = 128,
r = NULL, arguments.in.data = FALSE)
Data. Either a hyperframe
or a list of lists of point patterns.
Formula describing the grouping, when X
is a hyperframe.
The left side of the formula identifies which column of X
contains the point patterns.
The right side identifies the grouping factor.
If the formula is missing, the grouping variable is taken to be the
first column of X
that contains a factor, and the point
patterns are taken from the first column that contains point patterns.
Summary function applicable to point patterns.
Additional arguments passed to summaryfunction
.
Interval of distance values \(r\) over which the
summary function should be evaluated and over which the test
statistic will be integrated. If NULL
, the default
range of the summary statistic is used (taking the intersection
of these ranges over all patterns).
Number of random permutations for the test.
Logical value indicating choice of test statistic.
If TRUE
, use the alternative test statistic,
which is appropriate for summary functions with
roughly constant variance, such as \(K(r)/r\) or \(L(r)\).
Minimum permissible number of points in a point pattern for inclusion in the test calculation.
Number of discretisation steps in the rinterval
.
Optional vector of distance values as the argument for
summaryfunction
. Should not usually be given.
There is a sensible default.
Logical. If TRUE
, individual extra arguments to
summaryfunction
will be taken from X
(which must be a hyperframe). This assumes that
the first argument of summaryfunction
is the
point pattern dataset.
Object of class "studpermutest"
.
This function performs the studentized permutation test of Hahn (2012) for a difference between groups of point patterns.
The first argument X
should be either
Each element of X
will be interpreted as a group of
point patterns, assumed to be replicates of the same point process.
One column of the hyperframe should contain point patterns,
and another column should contain a factor indicating the
grouping. The argument formula
should be a formula in the
R language specifying the grouping: it should be of the form
P ~ G
where P
is the name of the column of point
patterns, and G
is the name of the factor.
A group needs to contain at least two point patterns with at least
minpoints
points in each pattern.
The function returns an object of class "htest"
and "studpermutest"
that can be printed and plotted.
The printout shows the test result and \(p\)-value.
The plot shows the summary functions for the
groups (and the group means if requested).
Hahn, U. (2012) A studentized permutation test for the comparison of spatial point patterns. Journal of the American Statistical Association 107 (498), 754--764.
# NOT RUN {
np <- if(interactive()) 99 else 19
testpyramidal <- studpermu.test(pyramidal, Neurons ~ group, nperm=np)
testpyramidal
# }
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