quadrat.test.splitppp {spatstat} | R Documentation |
Performs a chi-squared test of Complete Spatial Randomness for each of the component patterns in a split point pattern.
## S3 method for class 'splitppp' quadrat.test(X, ...)
X |
A split point pattern (object of class |
... |
Arguments passed to |
The function quadrat.test
is generic, with methods for
point patterns (class "ppp"
), split point patterns
(class "splitppp"
) and point process models
(class "ppm"
).
If X
is a split point pattern, then for each of the
component point patterns (taken separately) we test
the null hypotheses of Complete Spatial Randomness.
The method quadrat.test.ppp
is applied to each
component point pattern.
The return value is a list of objects, each giving the result of one of the tests.
A list of objects, each giving the result of one of the
hypothesis tests. Each component object is of class "htest"
and "quadrat.test"
. The list itself is of class "listof"
so that it can be printed and plotted.
Adrian Baddeley Adrian.Baddeley@csiro.au http://www.maths.uwa.edu.au/~adrian/ and Rolf Turner r.turner@auckland.ac.nz
quadrat.test
,
quadratcount
,
quadrats
,
quadratresample
,
chisq.test
,
kstest
.
To test a Poisson point process model against a specific alternative,
use anova.ppm
.
data(humberside) qH <- quadrat.test(split(humberside), 2, 3) plot(qH) qH