| MultiStraussHard {spatstat} | R Documentation |
Creates an instance of the multitype/hard core Strauss point process model which can then be fitted to point pattern data.
MultiStraussHard(types, iradii, hradii)
types |
Vector of all possible types (i.e. the possible levels
of the marks variable in the data) |
iradii |
Matrix of interaction radii |
hradii |
Matrix of hard core radii |
This is a hybrid of the multitype Strauss process
(see MultiStrauss) and the hard core process
(case gamma = 0 of the Strauss process).
A pair of points
of types i and j
must not lie closer than h[i,j] units apart;
if the pair lies more than h[i,j] and less than
r[i,j] units apart, it
contributes a factor
gamma[i,j] to the probability density.
The matrices iradii and hradii
must be symmetric, with entries
which are either positive numbers or NA.
A value of NA indicates that no interaction term should be included
for this combination of types.
Note that only the interaction radii and hardcore radii
are specified in MultiStraussHard.
The canonical parameters log(beta[j])
and log(gamma[i,j])
are estimated by ppm(), not fixed in
MultiStraussHard().
An object of class "interact"
describing the interpoint interaction
structure of the multitype/hard core Strauss process with
interaction radii iradii[i,j]
and hard core radii hradii[i,j].
The argument types is interpreted as a
set of factor levels. That is,
in order that ppm can fit the multitype Strauss model
correctly to a point pattern X,
this must be a marked point pattern; the mark vector
X$marks must be a factor; and
the argument types must
equal levels(X$marks).
Adrian Baddeley adrian@maths.uwa.edu.au http://www.maths.uwa.edu.au/~adrian/ and Rolf Turner rolf@math.unb.ca http://www.math.unb.ca/~rolf
ppm,
pairwise.family,
ppm.object,
MultiStrauss,
Strauss
r <- matrix(3, nrow=2,ncol=2)
h <- matrix(c(1,2,2,1), nrow=2,ncol=2)
MultiStraussHard(1:2, r, h)
# prints a sensible description of itself
data(betacells)
r <- 30.0 * matrix(c(1,2,2,1), nrow=2,ncol=2)
h <- 15.0 * matrix(c(NA,1,1,NA), nrow=2,ncol=2)
ppm(betacells, ~1, MultiStraussHard(c("off","on"), r, h), rbord=60.0)
# fit the stationary multitype hardcore Strauss process to `betacells'