residuals.slrm: Residuals for Fitted Spatial Logistic Regression Model

In spatstat.model: Parametric Statistical Modelling and Inference for the 'spatstat' Family

Residuals for Fitted Spatial Logistic Regression Model

Description

Given a spatial logistic regression model fitted to a point pattern, compute the residuals for each pixel.

Usage

  ## S3 method for class 'slrm'
residuals(object,
                           type=c("raw", "deviance", "pearson", "working", 
                                  "response", "partial", "score"),
                           ...)

Arguments

object	The fitted point process model (an object of class "ppm") for which residuals should be calculated.
type	String (partially matched) indicating the type of residuals to be calculated.
...	Ignored.

Details

This function computes several kinds of residuals for the fit of a spatial logistic regression model to a spatial point pattern dataset.

The argument object must be a fitted spatial logistic regression model (object of class "slrm"). Such objects are created by the fitting algorithm slrm.

The residuals are computed for each pixel that was used to fit the original model. The residuals are returned as a pixel image (if the residual values are scalar), or a list of pixel images (if the residual values are vectors).

The type of residual is chosen by the argument type.

For a given pixel, suppose p is the fitted probability of presence of a point, and y is the presence indicator (equal to 1 if the pixel contains any data points, and equal to 0 otherwise). Then

• type="raw" or type="response" specifies the response residual

  r = y - p

• type="pearson" is the Pearson residual

  r_P = \frac{y - p}{\sqrt{p (1-p)}}

• type="deviance" is the deviance residual

  r_D = (-1)^{y+1} \sqrt{-2(y log p + (1-y) log(1-p))}

• type="score" specifies the score residuals

  r_S = (y-p) x

  where x is the vector of canonical covariate values for the pixel

• type="working" specifies the working residuals as defined in residuals.glm

• type="partial" specifies the partial residuals as defined in residuals.glm

Value

A pixel image (if the residual values are scalar), or a list of pixel images (if the residual values are vectors).

Author(s)

\adrian

See Also

residuals.glm, residuals.ppm

Examples

   d <- if(interactive()) 128 else 32
   H <- unmark(humberside)
   fit <- slrm(H ~ x + y, dimyx=d)

   plot(residuals(fit))

   plot(residuals(fit, type="score"))

spatstat.model documentation built on Sept. 30, 2024, 9:26 a.m.