[Scilab-users] needed: SciLab routine for generating Weibull random variables with prior given autocorrelation

[Heinz Nabielek]

Many thanks. <https://en.wikipedia.org/wiki/Autoregressive_model#Example:_An_AR(1)_process> works fine on an originating normal distribution [where i would not need it, because we have grand(n, "mn", Mean, Cov) in SciLab].

With an initiating U(-0.5, 0,5), however, I get a triangle function, but not a autocorrelated uniform random distribution.

What to do?
Heinz




> On 03.05.2018, at 11:37, Stéphane Mottelet <stephane.mottelet at utc.fr> wrote:
> 
> Why don't start with a simple autoregressive process ? See e.g.
> 
> https://en.wikipedia.org/wiki/Autoregressive_model
> 
> 
> Le 03/05/2018 à 11:15, Heinz Nabielek a écrit :
>> Uniform U(0,1) random deviates with given autocorrelation would be good enough…...
>> 
>> 
>>> On 03.05.2018, at 10:57, Heinz Nabielek <heinznabielek at me.com> wrote:
>>> 
>>> Friends:
>>> 
>>> urgently needed: a SciLab routine for generating Weibull random variables with prior given autocorrelation.
>>> 
>>> Uncorrelated is easy with
>>> vc*((-log(grand(1,5,"def"))).^(1/m)) producing
>>> 0.9666848   1.4646143   10.402793   5.9513675   3.3241823
>>> with characteristic velocity vc=7 and modulus m=2.
>>> 
>>> But I need Weibull deviates with given autocorrelation, say rho=0.80
>>> 
>>> Literature has dozen of references on the subject which either do not work or I do not know how to code.
>>> 
>>> Any help here?
>>> Heinz