On 21/08/2009, at 3:30 PM, David Winsemius wrote:
On Aug 20, 2009, at 4:31 PM, kfcnhl wrote:
What is
1. par.ests <- optimfit$par
Just a guess... the parameter estimates from an optimization
procedure?
2. fisher <- hessb(negloglik, par.ests, maxvalue=maxima);
Probably the Fisher Information matrix.
3. varcov <- solve(fisher);
I seem to remember being told that the inverse of the Fisher
Information matrix gives you the variance covariance matrix.
4. par.ses <- sqrt(diag(varcov));
And the square roots of the diagonal elements of the variance-
covariance matrix would be the standard errors of the parameter
estimates.
Is the pop quiz over?
You might also have asked him ``Would you like coffee with that?'' :-)
cheers,
Rolf Turner
######################################################################
Attention:\ This e-mail message is privileged and confid...{{dropped:9}}
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
