Bread for Sandwich Estimator
Extracting an estimator for the ‘bread’ of the sandwich estimator,
see bread.
## S3 method for class 'maxLik' bread( x, ... )
x |
an object of class |
... |
further arguments (currently ignored). |
Matrix, the inverse of the expectation of the second derivative (Hessian matrix) of the log-likelihood function with respect to the parameters. In case of the simple Maximum Likelihood, it is equal to the variance covariance matrix of the parameters, multiplied by the number of observations.
The sandwich package is required for this function.
This method works only if the observaton-specific gradient information
was available for the estimation. This is the case if the
observation-specific gradient was supplied (see the grad
argument for maxLik), or the log-likelihood function
returns a vector of observation-specific values.
Arne Henningsen
## ML estimation of exponential duration model: t <- rexp(100, 2) loglik <- function(theta) log(theta) - theta*t ## Estimate with numeric gradient and hessian a <- maxLik(loglik, start=1 ) # Extract the "bread" library( sandwich ) bread( a ) all.equal( bread( a ), vcov( a ) * nObs( a ) )
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