Coefficients of Fitted Point Process Model
Given a point process model fitted to a point pattern,
extract the coefficients of the fitted model.
A method for coef.
## S3 method for class 'ppm' coef(object, ...)
object |
The fitted point process model (an object of class |
... |
Ignored. |
This function is a method for the generic function coef.
The argument object must be a fitted point process model
(object of class "ppm"). Such objects are produced by the maximum
pseudolikelihood fitting algorithm ppm).
This function extracts the vector of coefficients of the fitted model. This is the estimate of the parameter vector θ such that the conditional intensity of the model is of the form
λ(u,x) = exp(θ . S(u,x))
where S(u,x) is a (vector-valued) statistic.
For example, if the model object is the uniform Poisson process,
then coef(object) will yield a single value
(named "(Intercept)") which is the logarithm of the
fitted intensity of the Poisson process.
Use print.ppm to print a more useful
description of the fitted model.
A vector containing the fitted coefficients.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
and Rolf Turner r.turner@auckland.ac.nz
data(cells)
poi <- ppm(cells, ~1, Poisson())
coef(poi)
# This is the log of the fitted intensity of the Poisson process
stra <- ppm(cells, ~1, Strauss(r=0.07))
coef(stra)
# The two entries "(Intercept)" and "Interaction"
# are respectively log(beta) and log(gamma)
# in the usual notation for Strauss(beta, gamma, r)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.