spatstat.core (version 2.0-0)

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)

Arguments

object

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

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.

Value

A single numeric value.

Details

The function pseudoR2 is generic, with methods for fitted point process models of class "ppm".

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.

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)
# }