vcov.kppm {spatstat}R Documentation

Variance-Covariance Matrix for a Fitted Cluster Point Process Model

Description

Returns the variance-covariance matrix of the estimates of the parameters of a fitted cluster point process model.

Usage

   ## S3 method for class 'kppm'
vcov(object, ...,
          what=c("vcov", "corr", "fisher", "internals"))

Arguments

object

A fitted cluster point process model (an object of class "kppm".)

...

Ignored.

what

Character string (partially-matched) that specifies what matrix is returned. Options are "vcov" for the variance-covariance matrix, "corr" for the correlation matrix, and "fisher" for the Fisher information matrix.

Details

This function computes the asymptotic variance-covariance matrix of the estimates of the canonical (regression) parameters in the cluster point process model object. It is a method for the generic function vcov.

The result is an n * n matrix where n = length(coef(model)).

Value

A square matrix.

Author(s)

Abdollah Jalilian and Rasmus Waagepetersen. Ported to spatstat by Adrian Baddeley Adrian.Baddeley@csiro.au

References

Waagepetersen, R. (2007) Estimating functions for inhomogeneous spatial point processes with incomplete covariate data. Biometrika 95, 351–363.

See Also

kppm, vcov, vcov.ppm

Examples

   data(redwood)
   fit <- kppm(redwood, ~ x + y)
   vc <- vcov(fit)
   sd <- sqrt(diag(vc))
   t(coef(fit) + 1.96 * outer(sd, c(lower=-1, upper=1)))
   vcov(fit, what="corr")

[Package spatstat version 1.25-3 Index]