## S3 method for class 'ppm':
vcov(object, \dots, what = "vcov", verbose = TRUE)
"ppm"
.)"vcov"
for the variance-covariance matrix,
"corr"
for the correlation matrix, and
"fisher"
or "Fisher"
TRUE
, a message will be printed
if various minor problems are encountered.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.
X <- rpoispp(42)
fit <- ppm(X, ~ x + y)
vcov(fit)
vcov(fit, what="Fish")
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