spatstat.local (version 4.1-5)

loccit: Locally Fitted Cluster or Cox Point Process Model

Description

Fits a Neyman-Scott cluster process or Cox point process model using a locally-weighted composite likelihood.

Usage

loccit(X, trend = ~1,
       clusters = c("Thomas", "MatClust", "Cauchy", "VarGamma", "LGCP"),
       covariates = NULL,
       ...,
       diagnostics = FALSE,
       taylor = FALSE,
       sigma = NULL, f = 1/4,
       clustargs = list(), control = list(), 
       rmax,
       covfunargs=NULL, use.gam=FALSE, nd=NULL, eps=NULL,
       niter=3,
       fftopt = list(),
       verbose = TRUE)

Value

An object of class "loccit".

Arguments

X

Point pattern.

trend

Formula (without a left hand side) specifying the form of the logarithm of the intensity.

clusters

Character string determining the cluster model. Partially matched.

covariates

The values of any spatial covariates (other than the Cartesian coordinates) required by the model. A named list of pixel images, functions, windows or numeric constants.

diagnostics

Whether to perform auxiliary calculations in addition to the local estimates of the model parameters.

...

Additional arguments passed to as.mask to control the spatial resolution in the Fast Fourier Transform.

taylor

Logical value indicating whether to fit the model exactly at each spatial location (taylor=FALSE, the default) or to compute a first-order Taylor approximation to the fitted parameters (taylor=TRUE). The Taylor approximation is much faster.

sigma

Standard deviation of Gaussian kernel for local likelihood.

f

Argument passed to bw.frac to compute a value for sigma if it is missing or NULL.

clustargs

List of additional parameters for the cluster model, passed to the function RFcov in the RandomFields package.

control

List of control arguments passed to the generic optimisation function optim.

rmax

Maximum distance between pairs of points that will contribute to the composite likelihood.

covfunargs,use.gam,nd,eps

Arguments passed to ppm to control the intensity model and intensity fitting.

niter

Number of iterations in algorithm if taylor=FALSE.

fftopt

Developer use only.

verbose

Logical. If TRUE, print progress reports.

Author

Adrian Baddeley .

Details

This function fits a Cox or cluster process model to point pattern data locally, using the local Palm likelihood technique (Baddeley, 2016, section 8).

It can be used in the same way as kppm and effectively performs local fitting of the same model.

References

Baddeley, A. (2017) Local composite likelihood for spatial point patterns. Spatial Statistics, In press. DOI: 10.1016/j.spasta.2017.03.001

Baddeley, A., Rubak, E. and Turner, R. (2015) Spatial Point Patterns: Methodology and Applications with R. Chapman and Hall/CRC Press.

See Also

locppm

Examples

   X <- redwood[owin(c(0,1), c(-1,-1/2))]
   fit <- loccit(X, ~1, "Thomas", nd=5, control=list(maxit=20))
   fit