R: Calculate Pseudo-R-Squared for Point Process Model

pseudoR2 {spatstat.core} | 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 `"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`.

### 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 - D/D0

where D is the deviance of the fitted model `object`, and D0 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 r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.

### See Also

`deviance.ppm`, `deviance.slrm`.

### 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)

[Package spatstat.core version 2.4-4 Index]