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a method of estimating parameters of a statistical model by choosing the parameter value that optimizes the probability of observing the given sample.
1
vote
Accepted
The vcov function cannot be applied?
Actually you already have the S.E. for zeta and delta, calculated from log(zeta) and log(delta), in summary(hyperbfitalv): Variance-covariance matrix of the parameter estimates wrongly calculated?
Le …
2
votes
The vcov function cannot be applied?
The reason that parameters passed to the optimizer are pi, log(zeta), log(delta), mu not zeta and delta is mostly likely to constrain the optimizer in R+ for zeta and delta. If you need the Hessian of …
1
vote
Variance-covariance matrix of the parameter estimates wrongly calculated?
Seconded to @Jen 's answer. In fact the 5th line in the result of summary(hyperbfitalv) are SE's. They are indeed the square root of the diagonal elements of inverse-hessian solve(hyperbfitalv$hessian …