PairPiece | R Documentation |
Creates an instance of a pairwise interaction point process model with piecewise constant potential function. The model can then be fitted to point pattern data.
PairPiece(r)
r |
vector of jump points for the potential function |
A pairwise interaction point process in a bounded region is a stochastic point process with probability density of the form
f(x_1,…,x_n) = alpha . product { b(x[i]) } product { h(x_i, x_j) }
where x[1],…,x[n] represent the points of the pattern. The first product on the right hand side is over all points of the pattern; the second product is over all unordered pairs of points of the pattern.
Thus each point x[i] of the pattern contributes a factor b(x[i]) to the probability density, and each pair of points x[i], x[j] contributes a factor h(x[i], x[j]) to the density.
The pairwise interaction term h(u, v) is called piecewise constant if it depends only on the distance between u and v, say h(u,v) = H(||u-v||), and H is a piecewise constant function (a function which is constant except for jumps at a finite number of places). The use of piecewise constant interaction terms was first suggested by Takacs (1986).
The function ppm()
, which fits point process models to
point pattern data, requires an argument
of class "interact"
describing the interpoint interaction
structure of the model to be fitted.
The appropriate description of the piecewise constant pairwise
interaction is yielded by the function PairPiece()
.
See the examples below.
The entries of r
must be strictly increasing, positive numbers.
They are interpreted as the points of discontinuity of H.
It is assumed that H(s) =1 for all s > rmax
where rmax is the maximum value in r
. Thus the
model has as many regular parameters (see ppm
)
as there are entries in r
. The i-th regular parameter
theta[i] is the logarithm of the value of the
interaction function H on the interval
[r[i-1],r[i]).
If r
is a single number, this model is similar to the
Strauss process, see Strauss
. The difference is that
in PairPiece
the interaction function is continuous on the
right, while in Strauss
it is continuous on the left.
The analogue of this model for multitype point processes has not yet been implemented.
An object of class "interact"
describing the interpoint interaction
structure of a point process. The process is a pairwise interaction process,
whose interaction potential is piecewise constant, with jumps
at the distances given in the vector r.
and \rolf
Takacs, R. (1986) Estimator for the pair potential of a Gibbsian point process. Statistics 17, 429–433.
ppm
,
pairwise.family
,
ppm.object
,
Strauss
rmh.ppm
PairPiece(c(0.1,0.2)) # prints a sensible description of itself data(cells) ppm(cells ~1, PairPiece(r = c(0.05, 0.1, 0.2))) # fit a stationary piecewise constant pairwise interaction process # ppm(cells ~polynom(x,y,3), PairPiece(c(0.05, 0.1))) # nonstationary process with log-cubic polynomial trend
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