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 <ruettena...@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-boun...@r-project.org> On Behalf Of Amitha > Puranik > Sent: 22 August 2019 17:19 > To: r-sig-geo@r-project.org > Cc: c8a2375d-efb5-2ebe-7b3b-ac966d188...@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. > > > > > > > > > > > > > > > > On Thu, Aug 22, 2019 at 7:06 PM Roger Bivand <roger.biv...@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-ac966d188...@cirad.fr > > Kopi: r-sig-geo@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]] > > _______________________________________________ R-sig-Geo mailing list > > R-sig-Geo@r-project.org > > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > > > > > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > > [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
