maxLik (version 1.5-2.1)

vcov.maxLik: Variance Covariance Matrix of maxLik objects

Description

Extract variance-covariance matrices from maxLik objects.

Usage

# S3 method for maxLik
vcov( object, eigentol=1e-12, ... )

Value

the estimated variance covariance matrix of the coefficients. In case of the estimated Hessian is singular, it's values are

Inf. The values corresponding to fixed parameters are zero.

Arguments

object

a ‘maxLik’ object.

eigentol

eigenvalue tolerance, controlling when the Hessian matrix is treated as numerically singular.

...

further arguments (currently ignored).

Author

Arne Henningsen, Ott Toomet

Details

The standard errors are only calculated if the ratio of the smallest and largest eigenvalue of the Hessian matrix is less than “eigentol”. Otherwise the Hessian is treated as singular.

See Also

vcov, maxLik.

Examples

## ML estimation of exponential random variables
t <- rexp(100, 2)
loglik <- function(theta) log(theta) - theta*t
gradlik <- function(theta) 1/theta - t
hesslik <- function(theta) -100/theta^2
## Estimate with numeric gradient and hessian
a <- maxLik(loglik, start=1, control=list(printLevel=2))
vcov(a)
## Estimate with analytic gradient and hessian
a <- maxLik(loglik, gradlik, hesslik, start=1)
vcov(a)