pseudoR2 {spatstat.model} | R Documentation |
Calculate Pseudo-R-Squared for Point Process Model
Description
Given a fitted point process model, calculate the pseudo-R-squared value, which measures the fraction of variation in the data that is explained by the model.
Usage
pseudoR2(object, ...)
## S3 method for class 'ppm'
pseudoR2(object, ..., keepoffset=TRUE)
## S3 method for class 'slrm'
pseudoR2(object, ..., keepoffset=TRUE)
Arguments
object |
Fitted point process model.
An object of class |
keepoffset |
Logical value indicating whether to retain offset terms in the model when computing the deviance difference. See Details. |
... |
Additional arguments passed to
|
Details
The function pseudoR2
is generic, with methods
for fitted point process models
of class "ppm"
and "slrm"
.
This function computes McFadden's pseudo-Rsquared
R^2 = 1 - \frac{D}{D_0}
where D
is the deviance of the fitted model object
,
and D_0
is the deviance of the null model.
Deviance is defined as twice the negative log-likelihood
or log-pseudolikelihood.
The null model is usually obtained by re-fitting the model
using the trend formula ~1
.
However if the original model formula included offset
terms,
and if keepoffset=TRUE
(the default),
then the null model formula consists of these offset terms. This
ensures that the pseudoR2
value is non-negative.
Value
A single numeric value.
Author(s)
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner rolfturner@posteo.net and Ege Rubak rubak@math.aau.dk.
See Also
Examples
fit <- ppm(swedishpines ~ x+y)
pseudoR2(fit)
xcoord <- as.im(function(x,y) x, Window(swedishpines))
fut <- ppm(swedishpines ~ offset(xcoord/200) + y)
pseudoR2(fut)