Diggle-Gratton model
Creates an instance of the Diggle-Gratton pairwise interaction point process model, which can then be fitted to point pattern data.
DiggleGratton(delta=NA, rho)
delta |
lower threshold δ |
rho |
upper threshold ρ |
Diggle and Gratton (1984, pages 208-210) introduced the pairwise interaction point process with pair potential h(t) of the form
h(t) = ((t - δ)/(ρ - δ))^κ, { } δ ≤ t ≤ ρ
with h(t) = 0 for t < δ and h(t) = 1 for t > ρ. Here δ, ρ and κ are parameters.
Note that we use the symbol κ where Diggle and Gratton (1984) and Diggle, Gates and Stibbard (1987) use β, since in spatstat we reserve the symbol β for an intensity parameter.
The parameters must all be nonnegative, and must satisfy δ ≤ ρ.
The potential is inhibitory, i.e.\ this model is only appropriate for regular point patterns. The strength of inhibition increases with κ. For κ=0 the model is a hard core process with hard core radius δ. For κ=Inf the model is a hard core process with hard core radius ρ.
The irregular parameters
δ, ρ must be given in the call to
DiggleGratton
, while the
regular parameter κ will be estimated.
If the lower threshold delta
is missing or NA
,
it will be estimated from the data when ppm
is called.
The estimated value of delta
is the minimum nearest neighbour distance
multiplied by n/(n+1), where n is the
number of data points.
An object of class "interact"
describing the interpoint interaction
structure of a point process.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk
Diggle, P.J., Gates, D.J. and Stibbard, A. (1987) A nonparametric estimator for pairwise-interaction point processes. Biometrika 74, 763 – 770.
Diggle, P.J. and Gratton, R.J. (1984) Monte Carlo methods of inference for implicit statistical models. Journal of the Royal Statistical Society, series B 46, 193 – 212.
ppm(cells ~1, DiggleGratton(0.05, 0.1))
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.