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 missummaryfunction
.NULL
, the default
range of the summary statistic is used (taking the intersection
of 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 pa"studpermutest"
. The first argument X
should be either
[object Object],[object Object]
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).
testpyramidal <- studpermu.test(pyramidal, Neurons ~ group)
Run the code above in your browser using DataCamp Workspace