R: Variance-Covariance Matrix for a Fitted Cluster Point Process...

vcov.kppm {spatstat.core} | 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"),
              fast = NULL, rmax = NULL, eps.rmax = 0.01,
              verbose = TRUE)

### 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.
`fast` | Logical specifying whether tapering (using sparse matrices from Matrix) should be used to speed up calculations. Warning: This is expected to underestimate the true asymptotic variances/covariances.
`rmax` | Optional. The dependence range. Not usually specified by the user. Only used when `fast=TRUE`.
`eps.rmax` | Numeric. A small positive number which is used to determine `rmax` from the tail behaviour of the pair correlation function when fast option (`fast=TRUE`) is used. Namely `rmax` is the smallest value of r at which (g(r)-1)/(g(0)-1) falls below `eps.rmax`. Only used when `fast=TRUE`. Ignored if `rmax` is provided.
`verbose` | Logical value indicating whether to print progress reports during very long calculations.

### 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))`.

To calculate a confidence interval for a regression parameter, use `confint` as shown in the examples.

### Value

A square matrix.

### Author(s)

Abdollah Jalilian and Rasmus Waagepetersen. Ported to spatstat by Adrian Baddeley Adrian.Baddeley@curtin.edu.au and Ege Rubak rubak@math.aau.dk.

### 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

       fit <- kppm(redwood ~ x + y)
       vcov(fit)
       vcov(fit, what="corr")

       # confidence interval
       confint(fit)
       # cross-check the confidence interval by hand:
       sd <- sqrt(diag(vcov(fit)))
       t(coef(fit) + 1.96 * outer(sd, c(lower=-1, upper=1)))

[Package spatstat.core version 2.3-1 Index]