[R] Fitting a Weibull/NaNs

[Eric Rescorla]

Spencer Graves <spencer.graves at pdf.com> writes:
>       Bates and Watts (1988) Nonlinear Regression Analysis and Its
>       Applications (Wiley) explain that parameter effects curvature
>       seems to be vastly greater than the "intrinsic curvature" of the
>       nonlinear manifold, onto which a response vector is projected by
>       nonlinear least square.  This is different from maximum
>       likelihood, but I believe that this principle would still likely
>       apply.     Does this make sense?     spencer graves
Some :)

>          p.s.  I don't understand what you are saying about "0.41 3.70
>          1.00" below.  You are giving me a set of three numbers when
>          you are trying to estimate two parameters and getting NAs,
>          Inf's and NaNs.  I don't understand.  Are you printing out
>          "x" when the log(likelihood) is NA, NaN or Inf?  If yes, is
>          one component of "x" <= 0? Eric Rescorla wrote:
Doh! Typographical error to R. I had the "hessian=TRUE" clause inside
the c(). Doesn't make any difference for the results, though.

I'm doing the following:

> llfunc <-
+   function (zzz) {
+     tmp <- -sum(dweibull(d$Age.Month,shape=exp(zzz[1]),scale=exp(zzz[2]), log=TRUE))
+      if(is.infinite(tmp) | is.na(tmp)) { print(zzz);}
+     tmp
+ 
+   }
> mle <- nlm(llfunc,c(shape=.37,scale=4.0), hessian=TRUE)
[1] 0.37 4.00
[1] 0.37 4.00
[1] 0.370001 4.000000
[1] 0.370000 4.000004
[1] 0.3701 4.0000
[1] 0.3700 4.0004
[1] 0.3702 4.0000
[1] 0.3701 4.0004
[1] 0.3700 4.0008
Warning messages: 
1: NA/Inf replaced by maximum positive value 
2: NA/Inf replaced by maximum positive value 
3: NA/Inf replaced by maximum positive value 
4: NA/Inf replaced by maximum positive value 
5: NA/Inf replaced by maximum positive value 
6: NA/Inf replaced by maximum positive value 
7: NA/Inf replaced by maximum positive value 
8: NA/Inf replaced by maximum positive value 

I'm a little vague on how this is supposed to work, but when
I just compute 

        -sum(dweibull(d$Age.Month,shape=1.5,scale=40,log=TRUE))

I get "Inf". 

The problem seems to be that some of the values of d$Age.Month are 0
and since the Weibull always has a value of 0 at 0, the log likelihood
comes out insane. (I'm getting 0 values due to quantization error). 
OTOH when I remove the 0 values it works great, but that seems
kind of ad hoc. Is there some standard fix for this? 

Thanks much,
-Ekr


-- 
[Eric Rescorla                                   ekr at rtfm.com]
                http://www.rtfm.com/