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Ed,
An alternative is to import a CSV with numbers generated by any
theoretical distribution you like (you can generate these in XL for
example, see "Random Number Generator"). Then you can use AFL's
looping and Random to draw from this series.
I've asked Tomasz to increase the number of statistical/methematical
functions, because I now need to either program them myself (which is
complicated for something like multiple var OLS), or import from
external programs.
Hope this helps.
PS
--- In amibroker@xxxxxxxxxxxxxxx, "ed nl" <ed2000nl@xxxx> wrote:
> hi,
>
> the random() function generates numbers between 0 and 1,
distributed "linearly" (not sure this is the proper term ->
statistics was a while back .....). Meaning that if you run Lastvalue
(random()) a million times we would about get the same hits with 0.9
as with 0.3.
>
> (0.5 - Random()) * 2 gives you a function with numbers between -1
and 1 with a "linear" distribution.
>
> What I want is to generate random numbers between -1 and 1 which do
not have a "linear" distribution. They should have some kind of
Gaussian distribution where chances a number generated near 0 is
greater than a number generated neat -1 or 1.
>
> I made this Gauss function (see below) but this generates numbers
with a standard deviation of 1 but does not have a high or low number
restriction. So I want the numbers to fluctuate randomly between -1
and 1 but still have some form of Gauss function in them so that a
hit at 1 occurs less frequent than at 0.3.
>
> thanks,
>
> rgds, Ed
>
>
> function gauss_func() {
>
> w = 1;
> while( w >= 1 ) {
>
> x1 = 2.0 * LastValue(Random()) - 1;
> x2 = 2.0 * LastValue(Random()) - 1;
> w = x1 * x1 + x2 * x2;
>
> }
>
> w = sqrt( (-2 * log(w)) / w );
> y1 = x1 * w;
> //y2 = x2 * w;
>
> return y1;
>
> }
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