# Re: R-beta: SEs for one-param MLE in R?

Martin Maechler (maechler@stat.math.ethz.ch)
Tue, 14 Apr 1998 18:22:12 +0200

```Date: Tue, 14 Apr 1998 18:22:12 +0200
Message-Id: <199804141622.SAA01845@sophie.ethz.ch>
From: Martin Maechler <maechler@stat.math.ethz.ch>
To: wsimpson@uwinnipeg.ca
Subject: Re: R-beta: SEs for one-param MLE in R?

>>>>> "Bill" == Bill Simpson <wsimpson@uwinnipeg.ca> writes:

Bill> Simple-mindedly I tried getting MLE and SE for one-parameter
Bill> model in the same way as for multi-param models.

Bill> out<-nlm(fn,p=c(2),hessian=T)

Bill> But sqrt(diag(solve(out\$hessian))) gives the answer 1.  The
Bill> Hessian has only one entry, not really a matrix.  diag(x) gives 1
Bill> if x is just a single number.

Bill> Is this what I should be doing to get SE for MLE?
Bill> sqrt(solve(out\$hessian))

Bill> Thanks very much for any help!

Well,
.Internal(nlm(..)) should be fixed to always return a matrix in  \$ hessian.

However, your problem is solved easily by always using

p <- length(estimate)
SE <- sqrt(if(p==1) 1/out\$hessian else diag(solve(out\$hessian)))

BTW: I am (we are) interested in the functions that you are writing for nlm(.)
It certainly is worthwhile to have nlm(.) return a class "nlm" result
and provide  print.nlm(.) and summary.nlm(.) functions
{{ Jim Lindsey already posted something like this, unfortunately using
"nls" which we don't want as long as it is not very close to S'
nls(.) function
}}

Martin
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