[R-sig-Geo] Simulating variables with predefined correlation and autocorrelation

[Amitha Puranik]

Dear Dr Tobias,

Thanks a lot for sharing the materials. This means a lot!












On Tue, Sep 3, 2019 at 1:05 PM Tobias Rüttenauer <ruettenauer using sowi.uni-kl.de>
wrote:

> Dear Amitha,
>
> If understand your query correctly, you could also have a look at my
> preprint on Monte Carlo simulations of different spatial regression models:
> https://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/5630.
>
> The replication materials are online available (
> https://github.com/ruettenauer/Reproduction-Material-Spatial-Monte-Carlo-Experiments).
> The '01_Monte Carlo Simulation Spatial_Program.R' scipt provides a function
> to set up data with different constellations of autocorrelation. Maybe the
> code is useful for your purposes as well.
>
> Best,
> Tobias
>
>
> -----Original Message-----
> From: R-sig-Geo <r-sig-geo-bounces using r-project.org> On Behalf Of Amitha
> Puranik
> Sent: 22 August 2019 17:19
> To: r-sig-geo using r-project.org
> Cc: c8a2375d-efb5-2ebe-7b3b-ac966d188f53 using cirad.fr
> Subject: Re: [R-sig-Geo] Simulating variables with predefined correlation
> and autocorrelation
>
> Dear Prof. Bivand,
>
>
>
> Thanks a lot for responding and providing the material to read. I will
> definitely go through your paper and the references cited in it.
>
> I am working on simulating various scenarios where autocorrelation exists
> in Y or X or both and also in the residuals and compare the model
> performances on these data. At present I have planned to assign same
> weights (distance based) for both X and Y. I have found solution to
> simulate autocorrelated Y based on your response in the link (
> https://stat.ethz.ch/pipermail/r-sig-geo/2011-September/012728.html). But
> I have not found a way to induce autocorrelation in even the independent
> variables(s). Hence I posted this query. Thanks in advance.
>
> Regards,
>
> Amitha Puranik.
>
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> On Thu, Aug 22, 2019 at 7:06 PM Roger Bivand <Roger.Bivand using nhh.no> wrote:
>
> > Could you please explain why you want to do this and whether you want
> > to use the same weights for y and x? Maybe refer to
> > https://doi.org/10.1111/j.1538-4632.1991.tb00235.x and work referred
> > to there; I'll try to find other references later.
> >
> > Roger Bivand
> > Norwegian School of Economics
> > Bergen, Norway
> >
> >
> >
> > Fra: Amitha Puranik
> > Sendt: torsdag 22. august, 12.41
> > Emne: Re: [R-sig-Geo]  Simulating variables with predefined
> > correlation and autocorrelation
> > Til: c8a2375d-efb5-2ebe-7b3b-ac966d188f53 using cirad.fr
> > Kopi: r-sig-geo using r-project.org
> >
> >
> > Dear Prof Facundo Muñoz, Thank you for a quick response. I am sorry
> > for not phrasing my query clearly. I am interested to simulate 2
> > variables Y and X in such a way that the resultant variables should
> > possess the correlation coefficient of 0.6 between Y and X and
> > autocorrelation of 0.7 in Y and 0.4 in X. The query posted in the link
> > (
> > https://stat.ethz.ch/pipermail/r-sig-geo/2011-September/012728.html)
> > focussed on only the autocorrelation of Y (spatial lag model) whereas
> > I would like to introduce some autocorrelation in X too (spatial
> > durbin model). Is there a way to do this? Should a covariance
> > structure defining both correlation and autocorrelation be specified
> > while simulating variables? If so, how to define such covariance
> > structure? I will be grateful for your assistance. Thanks in advance.
> > Amitha Puranik [[alternative HTML version deleted]]
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> > R-sig-Geo using r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
> >
>
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>
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