Variance-Covariance Matrix for a Fitted Spatial Logistic Regression
Returns the variance-covariance matrix of the estimates of the parameters of a point process model that was fitted by spatial logistic regression.
## S3 method for class 'slrm' vcov(object, ..., what=c("vcov", "corr", "fisher", "Fisher"))
object |
A fitted point process model of class |
... |
Ignored. |
what |
Character string (partially-matched)
that specifies what matrix is returned.
Options are |
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 "slrm"
, typically
produced by slrm
. It represents a Poisson point process
model fitted by spatial logistic regression.
The canonical parameters of the fitted model object
are the quantities returned by coef.slrm(object)
.
The function vcov
calculates the variance-covariance matrix
for these parameters.
The argument what
provides three options:
what="vcov"
return the variance-covariance matrix of the parameter estimates
what="corr"
return the correlation matrix of the parameter estimates
what="fisher"
return the observed Fisher information matrix.
Note that standard errors and 95% confidence intervals for
the coefficients can also be obtained using
confint(object)
or coef(summary(object))
.
Standard errors for the fitted intensity can be obtained
using predict.slrm
.
A square matrix.
An error message that reports system is computationally singular indicates that the determinant of the Fisher information matrix was either too large or too small for reliable numerical calculation. This can occur because of numerical overflow or collinearity in the covariates.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
and Rolf Turner r.turner@auckland.ac.nz .
Baddeley, A., Berman, M., Fisher, N.I., Hardegen, A., Milne, R.K., Schuhmacher, D., Shah, R. and Turner, R. (2010) Spatial logistic regression and change-of-support for spatial Poisson point processes. Electronic Journal of Statistics 4, 1151–1201. doi: 10.1214/10-EJS581
vcov
for the generic,
slrm
for information about fitted models,
predict.slrm
for other kinds of calculation about the model,
confint
for confidence intervals.
X <- rpoispp(42) fit <- slrm(X ~ x + y) vcov(fit) vcov(fit, what="corr") vcov(fit, what="f")
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