Performs a Monte Carlo test of spatial segregation of the types in a multitype point pattern.
segregation.test(X, ...)# S3 method for ppp
segregation.test(X, ..., nsim = 19,
permute = TRUE, verbose = TRUE, Xname)
An object of class "htest"
representing the result of the test.
Multitype point pattern (object of class "ppp"
with factor-valued marks).
Additional arguments passed to relrisk.ppp
to control the smoothing parameter or bandwidth selection.
Number of simulations for the Monte Carlo test.
Argument passed to rlabel
. If TRUE
(the
default), randomisation is performed by randomly permuting the
labels of X
. If FALSE
, randomisation is performing
by resampling the labels with replacement.
Logical value indicating whether to print progress reports.
Optional character string giving the name of the dataset X
.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner rolfturner@posteo.net and Ege Rubak rubak@math.aau.dk.
The Monte Carlo test of spatial segregation of types,
proposed by Kelsall and Diggle (1995)
and Diggle et al (2005), is applied to the point pattern X
.
The test statistic is
$$
T = \sum_i \sum_m \left( \widehat p(m \mid x_i) - \overline p_m
\right)^2
$$
where \(\widehat p(m \mid x_i)\) is the
leave-one-out kernel smoothing estimate of the probability that the
\(i\)-th data point has type \(m\), and
\(\overline p_m\) is the average fraction of data points
which are of type \(m\).
The statistic \(T\) is evaluated for the data and
for nsim
randomised versions of X
, generated by
randomly permuting or resampling the marks.
Note that, by default, automatic bandwidth selection will be
performed separately for each randomised pattern. This computation
can be very time-consuming but is necessary for the test to be
valid in most conditions. A short-cut is to specify the value of
the smoothing bandwidth sigma
as shown in the examples.
Kelsall, J.E. and Diggle, P.J. (1995) Kernel estimation of relative risk. Bernoulli 1, 3--16.
Diggle, P.J., Zheng, P. and Durr, P. (2005) Non-parametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK. Applied Statistics 54, 645--658.
relrisk
segregation.test(hyytiala, 5)
if(interactive()) segregation.test(hyytiala, hmin=0.05)
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