[Scilab-users] {EXT} Can you suggest a more efficient procedure for generating random variables?

[Claus Futtrup]

Hi there

Interesting ...

If this is excellent for Monte-Carlo simulations, I wish that such an 
example is put into the documentation. Lots of people (who need 
Monte-Carlo) would then accidentally fall over it and take advantage of it.

Cheers,
Claus

On 18.03.2019 11:06, Heinz Nabielek wrote:
> Ingenious. Works with precision. Gigantically fast for a million random deviates. Ideal for Monte-Carlo simulations.
>
> I had never heard of dsearch* before......
> Thanks a lot
> Heinz
>
>
> * I wished the Scilab help files would be more readable.....
>
>> On 18.03.2019, at 09:50, Dang Ngoc Chan, Christophe <Christophe.Dang at sidel.com> wrote:
>>
>> Hello Heinz,
>>
>>> De : Heinz Nabielek
>>> Envoyé : dimanche 17 mars 2019 23:50
>>>
>>> I need to generate random deviates x according to a given cumulative
>>> distribution y that is available only in tabular form.
>>> [...]
>>> for i=1:N;
>>> x=[x find(y>z(i),1)];
>>> end;
>>>
>>> y is a previously defined table with values monotonically increasing from zero
>> I guess these are quantiles.
>>
>> I think you can vectorise with something like
>>
>> x = dsearch(z, y)
>>
>> I tried a little bit and it seems to work but I don't know the exact application so...
>>
>> HTH
>>
>> --
>> Christophe Dang Ngoc Chan
>> Mechanical calculation engineer
>>
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