studpermu.test(X, formula, summaryfunction = Kest, ..., rinterval = NULL, nperm = 999, use.Tbar = FALSE, minpoints = 20, rsteps = 128, r = NULL, arguments.in.data = FALSE)hyperframe or a list of lists of point patterns.
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.
summaryfunction.
NULL, the default
range of the summary statistic is used (taking the intersection
of these ranges over all patterns).
TRUE, use the alternative test statistic,
which is appropriate for summary functions with
roughly constant variance, such as $K(r)/r$ or $L(r)$.
rinterval.
summaryfunction. Should not usually be given.
There is a sensible default.
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.
"studpermutest".
The first argument X should be either
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).
np <- if(interactive()) 99 else 19
testpyramidal <- studpermu.test(pyramidal, Neurons ~ group, nperm=np)
testpyramidal
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