# coef.ppm

##### 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`

.

##### Usage

```
# S3 method for 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 \(\theta\) such that the conditional intensity of the model is of the form $$ \lambda(u,x) = \exp(\theta S(u,x)) $$ 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.

##### See Also

##### Examples

```
# NOT RUN {
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)
# }
```

*Documentation reproduced from package spatstat, version 1.64-1, License: GPL (>= 2)*