| 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 probit or maxLik. |
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)