[R] weighted 2 or 3 parameter weibull estimation?

[ripley@stats.ox.ac.uk]

On Fri, 5 Apr 2002, Jeff D. Hamann wrote:

> Subject: Re: [R] weighted 2 or 3 parameter weibull estimation?
>
> Without knowing your cost function (i.e., that passed to optim) its hard
> to help.
>
> T.
>
>
> Here's what I used to obtain my estimates:
>
>
> # estimate the two parameter weibull
> loglike <- function(p) -2*sum(dweibull(expf,p[1],p[2],log=T))
> est <- optim( c(1,5), loglike )
>
> as I mentioned, I'm very much a newbie at using optim (and maybe less so
> with R), but I hope this help answer your question.

fitdistr in package MASS would be even easier.

I'm afraid I don't understand your weights here.  I can understand integer
weights (where weight 3 means `I have three cases like this one'), where
one just uses

loglike <- function(p, wt) -2*sum(wt * dweibull(expf,p[1],p[2],log=T))
est <- optim( c(1,5), loglike, wt=wt )

But your example looks much more like a bivariate problem.

>
> Thanks,
> Jeff.
>
>
>
> >   I've figured out how to use optim (barely) to estimate 2 parameter =
> >   weibull distributions. I can't get over how easy this is. What I need to
> =
> >   do is use a weight in the observations.....
> >
> >   For example,=20
> >
> >   the tree diameters and weights are are=20
> >
> >   4.70 , 100
> >   6.00, 98
> >   7.10,  75.0
> >   8.10, 86.3
> >   8.60, 80.456
> >   8.90, 20.5
> >   9.50, 16.6
> >   11.40, 12.657
> >   11.80, 12.47
> >   14.50, 8.98
> >   16.00,4.5
> >   16.90,2.36
> >   18.90, 0.256
> >
> >   which yield
> >
> >  LOCATION =3D   0.0000              MEAN =3D   10.9921
> >     SCALE =3D  12.3436          VARIANCE =3D   18.0027
> >     SHAPE =3D   2.8050          SKEWNESS =3D    0.2354
> >
> >   which are the values without the weights. I can't find any reference to
> =
> >   weights in the optim function and I'm afraid I'm a little stuck here. =
> >   After I figure out how to include the weights, I'll then need to =
> >   estimate the 3-parameter estimates. Any help would be greatful.=20
> >
> >   Thanks,
> >   Jeff.
>
>
>
> Jeff D. Hamann
> Hamann, Donald & Associates, Inc.
> PO Box 1421
> Corvallis, Oregon USA 97339-1421
> Bus. 541-753-7333
> Cell. 541-740-5988
> jeff_hamann at hamanndonald.com
> www.hamanndonald.com
>
>
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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