# logLik.slrm

##### Loglikelihood of Spatial Logistic Regression

Computes the (maximised) loglikelihood of a fitted Spatial Logistic Regression model.

##### Usage

```
## S3 method for class 'slrm':
logLik(object, ..., adjust = TRUE)
```

##### Arguments

- object
- a fitted spatial logistic regression model.
An object of class
`"slrm"`

. - ...
- Ignored.
- adjust
- Logical value indicating whether to adjust the loglikelihood of the model to make it comparable with a point process likelihood. See Details.

##### Details

This is a method for `logLik`

for fitted spatial logistic
regression models (objects of class `"slrm"`

, usually obtained
from the function `slrm`

). It computes the log-likelihood
of a fitted spatial logistic regression model.

If `adjust=FALSE`

, the loglikelihood is computed
using the standard formula for the loglikelihood of a
logistic regression model for a finite set of (pixel) observations.

If `adjust=TRUE`

then the loglikelihood is adjusted so that it
is approximately comparable with the likelihood of a point process
in continuous space, by subtracting the value
$n \log(a)$
where $n$ is the number of points in the original point pattern
dataset, and $a$ is the area of one pixel.

##### Value

- A numerical value.

##### See Also

##### Examples

```
X <- rpoispp(42)
fit <- slrm(X ~ x+y)
logLik(fit)
logLik(fit, adjust=FALSE)
```

*Documentation reproduced from package spatstat, version 1.23-3, License: GPL (>= 2)*