Re: st: creating a new user function in Stata

["Carlos Madeira" <carlos_m_madeira@hotmail.com>]

Hi Maarten,

thanks for your answer. I think it was very clear.

Actually, I didn't think before of the problem you pointed out with the 
small numbers, but I think I can find a way around it. I think the problem 
is that in general we define a beta function in the space [0-1], so if I 
think about it that will necessarily imply that the numbers involved for the 
standard-deviations and the correlation are very small. However, I think 
there is a simple way around that. If I translate my natural "beta-space" to 
be equivalent to [0-100], then perhaps things will work well.

Best,

Carlos






> From: Maarten buis <maartenbuis@yahoo.co.uk>
> Reply-To: statalist@hsphsun2.harvard.edu
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: creating a new user function in Stata
> Date: Sat, 10 Feb 2007 11:47:28 +0000 (GMT)
>
> --- Carlos Madeira <carlos_m_madeira@hotmail.com> wrote:
> > I had a problem writing a user-written function in Stata and was
> > wondering if you could give me a help about how to write it. My goal
> > is to create a program that generates a variable with cdf values of a
> > bivariate-beta function in a similar way that the function i
> > beta(a1,b1,x1) would do.
>
> Short answer is that functions are hard coded into Stata, so you can't
> write your own function. You can write an -egen- program. But given
> your example I suspect you want this to be part of a ml program. In
> that case I wouldn't bother and just break the equation up in manageble
> parts and create temporary variables. So looking at the equation you
> gave us:
> > cdf_biv_beta =
> > ibeta(a1,b1,x1)(1+w(x1-a1/(a1+b1))(x2-a2/(a2+b2))ibeta(a2,b2,x2) +
> > (....)
>
> I would do:
> tempvar mean1 mean2 temp
> gen double `mean1' = `a1'/(`a1' + `b1')
> gen double `mean2' = `a2'/(`a2' + `b2')
> gen double `temp' = 1 + `w'*(`x1'-`mean1')*(`x2'-`mean2')
> replace `lnf' = ln(ibeta(`a1',`b1',`x1') * /*
>                */  `temp' *                /*
>                */  ibeta(`a2',`b2',`x2') + /*
>                */  ... )
>
> I have two additional comments:
> 1. When writing down the log likelihood it is worth the effort to see
> if taking the log simplifies the equation (turns multiplications in
> additions, and the like). An example is shown in a short technical text
> on http://home.fsw.vu.nl/m.buis/software/betafit.html .
> 2. the part 1 + `w'*(`x1'-`mean1')*(`x2'-`mean2') worries me from a
> numerical point of view. `x1'-`mean1' is the difference between an
> observed and expected proportion, so this is usually a small number.
> You multiply it with a similarly small number: `x2'-`mean2'. Adding
> such a small number to 1 can lead to big rounding errors. The last Mata
> matters column in the Stata Journal (volume 6, number 4) by William
> Gould was very clear piece on this issue.
>
> Hope this helps,
> Maarten
>
>
> -----------------------------------------
> Maarten L. Buis
> Department of Social Research Methodology
> Vrije Universiteit Amsterdam
> Boelelaan 1081
> 1081 HV Amsterdam
> The Netherlands
>
> visiting address:
> Buitenveldertselaan 3 (Metropolitan), room Z434
>
> +31 20 5986715
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
>
>
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