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

[Heinz Nabielek]

CONF=.95, N=1432, n=1
cdfbet("XY", n+1, N+1-n, CONF, 1-CONF)

is doing it just fine. Correct and with high precision...
h


On 18.05.2020, at 18:09, Tim Wescott <tim at wescottdesign.com> wrote:
> 
> 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