vcov.maxLik: Variance Covariance Matrix of maxLik objects

In maxLik: Maximum Likelihood Estimation and Related Tools

Description

Extract variance-covariance matrices from maxLik objects.

Usage

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

Arguments

object	a ‘maxLik’ object.
eigentol	eigenvalue tolerance, controlling when the Hessian matrix is treated as numerically singular.
...	further arguments (currently ignored).

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.

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.

Author(s)

Arne Henningsen, Ott Toomet

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)

Example output

Loading required package: miscTools

Please cite the 'maxLik' package as:
Henningsen, Arne and Toomet, Ott (2011). maxLik: A package for maximum likelihood estimation in R. Computational Statistics 26(3), 443-458. DOI 10.1007/s00180-010-0217-1.

If you have questions, suggestions, or comments regarding the 'maxLik' package, please use a forum or 'tracker' at maxLik's R-Forge site:
https://r-forge.r-project.org/projects/maxlik/
----- Initial parameters: -----
fcn value: -54.79315 
     parameter initial gradient free
[1,]         1         45.20685    1
Condition number of the (active) hessian: 1 
-----Iteration 1 -----
-----Iteration 2 -----
-----Iteration 3 -----
-----Iteration 4 -----
-----Iteration 5 -----
--------------
gradient close to zero 
5  iterations
estimate: 1.825046 
Function value: -39.8395 
           [,1]
[1,] 0.03333432
           [,1]
[1,] 0.03330792

maxLik documentation built on Nov. 25, 2020, 3 a.m.