# vcov.ppm

##### Variance-Covariance Matrix for a Fitted Point Process Model

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

##### Usage

```
## S3 method for class 'ppm':
vcov(object, \dots, what = "vcov", verbose = TRUE)
```

##### Arguments

- object
- A fitted point process model (an object of class
`"ppm"`

.) - ...
- 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"`

or`"Fisher"`

- verbose
- Logical. If
`TRUE`

, a message will be printed if various minor problems are encountered.

##### Details

This function computes the asymptotic variance-covariance
matrix of the estimates of the canonical parameters in the
point process model `object`

. It is a method for the
generic function `vcov`

.

`object`

should be an object of class `"ppm"`

, typically
produced by `ppm`

. The current implementation only works
for Poisson point processes.

The canonical parameters of the fitted model `object`

are the quantities returned by `coef.ppm(object)`

.
The function `vcov`

calculates the variance-covariance matrix
for these parameters.
The argument `what`

provides three options:
[object Object],[object Object],[object Object]
The calculations are based on standard asymptotic theory for the maximum
likelihood estimator.
In all cases, the observed Fisher information matrix of the fitted model
`object`

is first computed, by
summing over the Berman-Turner quadrature points in the fitted model.
The asymptotic variance-covariance matrix is calculated as the inverse of the
observed Fisher information. The correlation matrix is then obtained
by normalising.

In all three cases, the result is a square matrix.
The rows and columns of the matrix correspond to the canonical
parameters given by `coef.ppm(object)`

. The row and column
names of the matrix are also identical to the names in
`coef.ppm(object)`

.

The argument `verbose`

makes it possible to suppress some
diagnostic messages.

##### Value

- A square matrix.

##### Examples

```
X <- rpoispp(42)
fit <- ppm(X, ~ x + y)
vcov(fit)
vcov(fit, what="Fish")
```

*Documentation reproduced from package spatstat, version 1.9-2, License: GPL version 2 or newer*