[Scilab-users] Can Scilab compute the inverse of the regularized Incomplete Beta Function?

[Tim Wescott]

So you have \beta(x, n+1, N+1-n) = 0.95, and you want to solve for x?

fsolve will do this for a single value of the confidence.  Is that
sufficient?

On Sun, 2020-05-17 at 23:49 +0200, Heinz Nabielek wrote:
> Dear SciLabers:
> 
> can Scilab compute the inverse of the regularized Incomplete Beta
> Function?
> 
> Example: in unbiased sampling in Austria with sample size N=1432,
> they detected n=1 infections.
> Therefore, expected infected fraction = 0.000698324.
> 
> But this does not say much, because the sample size was small and the
> "success" was extremely small (fortunately).
> 
> The standard procedure therefore is to derive the one-sided 95% upper
> confidence limit:
> CONF=0.95; N=1432; n=1:
> One-sided 95% upper confidence limit fraction = BETA.INV(CONF, n+1,
> N+1-n) = 0.003306121
> 
> How would I do that in Scilab?
> Heinz
> 
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-- 

Tim Wescott
www.wescottdesign.com
Control & Communications systems, circuit & software design.
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