Loglikelihood of Spatial Logistic Regression
Computes the (maximised) loglikelihood of a fitted Spatial Logistic Regression model.
## S3 method for class 'slrm': logLik(object, ..., adjust = TRUE)
- a fitted spatial logistic regression model.
An object of class
- Logical value indicating whether to adjust the loglikelihood of the model to make it comparable with a point process likelihood. See 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.
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.
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
where $n$ is the number of points in the original point pattern
dataset, and $a$ is the area of one pixel.
- A numerical value.
X <- rpoispp(42) fit <- slrm(X ~ x+y) logLik(fit) logLik(fit, adjust=FALSE)