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

[Federico Miyara]

Heinz,

I don't know if this will serve you, but you cn always approximate the 
inverse of a function using spline interpolation. If you have y(k) = 
f(x(k)) fo a range of values of x then you can interpolate the data y(k) 
x(k) for a value yo to get an xo that approximates finv(yo).

Regards

Federico Miyara




On 17/05/2020 18:49, 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
>
> _______________________________________________
> users mailing list
> users at lists.scilab.org
> http://lists.scilab.org/mailman/listinfo/users
>

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://lists.scilab.org/pipermail/users/attachments/20200517/9b3fd53c/attachment.htm>