estfun.maxLik {maxLik} | R Documentation |
Extract the gradients of the log-likelihood function evaluated
at each observation (‘Empirical Estimating Function’,
see estfun
).
## S3 method for class 'maxLik' estfun( x, ... )
x |
an object of class |
... |
further arguments (currently ignored). |
Matrix of gradients of the log-likelihood function at the estimated parameter value evaluated at each observation
The sandwich package must be loaded before this method can be used.
This method works only if maxLik
was called
with argument grad
equal to a gradient function or
(if no gradient function is specified)
argument logLik
equal to a log-likelihood function
that return the gradients or log-likelihood values, respectively,
for each observation.
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 gradients evaluated at each observation library( sandwich ) estfun( a ) ## Estimate with analytic gradient gradlik <- function(theta) 1/theta - t b <- maxLik(loglik, gradlik, start=1) estfun( b ) all.equal( c( estfun( b ) ), gradlik( coef( b ) ) )