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RE: [S] Fisher Information?

daemon@ATHENA.MIT.EDU (Annis, Charles G. Jr.)
Fri Sep 17 09:45:04 1999

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From: "Annis, Charles G. Jr." <annis@pwfl.com>
To: "'s-news@wubios.wustl.edu'" <s-news@wubios.wustl.edu>
Date: Fri, 17 Sep 1999 09:38:02 -0400
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Hi, Everybody:

Yesterday I asked: 
 
> How can I get at the Fisher Information matrix that I assume is an adjunct
> to the parameter estimation machinations carried out by the censored
> regression algorithms of Parametric Survival?

Terry M. Therneau answered for surveg:

>>> snip >>>>>>>>>>>>>>>>>>>>>>>>>>
For the survreg routine:
	fit <- survreg(Surv(time, status) ~ age + sex, data=lung)
the component fit$var contains the inverse Hessian.  So

> solve(fit$var)
            (Intercept)         age           sex   Log(scale) 
(Intercept)   290.19140   18364.717    383.404514    14.049320
        age 18364.71683 1183113.855  24198.547666  1128.508704
        sex   383.40451   24198.548    569.830738    -2.428344
 Log(scale)    14.04932    1128.509     -2.428344   271.049477

 is the matrix you are interested in.  Internally, the routine uses
log(scale) rather than scale as the parameter, because the iteration has
proven to be much more stable.
>>> snip >>>>>>>>>>>>>>>>>>>>>>>>>>>

The same method works for censorReg:

> fit<-censorReg(formula = censor(log10(FSH), censored, type = "right") ~
log10(diameter.size.) + ... etc.
> fit$var
                         (Intercept) log10(diameter.size.)          depth
System     Hole.Type1 
           (Intercept)  0.0315660536          0.01723570563 -0.00275711645
4.525893e-004 -0.00135281053
log10(diameter.size.)  0.0172357056          0.00990256667 -0.00029283235
2.346990e-004 -0.00046046000
                 depth -0.0027571165         -0.00029283235  0.00400469871
-2.177125e-005  0.00088403607
                System  0.0004525893          0.00023469904 -0.00002177125
2.434062e-004 -0.00001836242
            Hole.Type1 -0.0013528105         -0.00046046000  0.00088403607
-1.836242e-005  0.00068110472 etc.
 
produces the variance-covariance matrix, whose inverse is the Fisher
Information (Cramér-Rao inequality notwithstanding).

My thanks to Dr. Therneau for his help, and for the suggestions of Professor
Bill Meeker and Paul Monaghan.

Charles Annis, P.E.
AnnisC@ASME.org
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