R: Coefficients of Fitted Point Process Model

coef.ppm {spatstat} | R Documentation

## Coefficients of Fitted Point Process Model

### Description

Given a point process model fitted to a point pattern, extract the coefficients of the fitted model. A method for `coef`.

### Usage

      ## S3 method for class 'ppm'
    coef(object, ...)

### Arguments

`object` | The fitted point process model (an object of class `"ppm"`)
`...` | Ignored.

### Details

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.

### Value

A vector containing the fitted coefficients.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au

and Rolf Turner r.turner@auckland.ac.nz

### See Also

`print.ppm`, `ppm.object`, `ppm`

### Examples

        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)

[Package spatstat version 1.63-3 Index]