vcov.maxLik {maxLik} | R Documentation |
Extract variance-covariance matrices of objects of class maxLik
.
## S3 method for class 'maxLik' vcov( object, eigentol=1e-12, ... )
object |
an object of class |
eigentol |
nonzero print limit on the range of the absolute values of the hessian. Specifically, define: absEig <- eigen(hessian(object), symmetric=TRUE)[['values']] Then compute and print t values, p values, etc. only if min(absEig) > (eigentol * max(absEig)). |
... |
further arguments (currently ignored). |
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.
Arne Henningsen, Ott Toomet otoomet@ut.ee
## ML estimation of exponential duration model: 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, print.level=2) vcov(a) ## Estimate with analytic gradient and hessian a <- maxLik(loglik, gradlik, hesslik, start=1) vcov(a)