spatstat.core (version 2.3-1)

pseudoR2: 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 ppm
pseudoR2(object, …, keepoffset=TRUE)
  # S3 method for slrm
pseudoR2(object, …, keepoffset=TRUE)

Arguments

object

Fitted point process model. An object of class "ppm" or "slrm".

keepoffset

Logical value indicating whether to retain offset terms in the model when computing the deviance difference. See Details.

…

Additional arguments passed to deviance.ppm or deviance.slrm.

Value

A single numeric value.

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.

See Also

deviance.ppm, deviance.slrm.

Examples

# NOT RUN {
  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)
# }