[R-sig-Geo] Bayesian Estimates for 1st-order Spatial Autoregressive Model

[Eelke Folmer]

Hi,
I think you might be interested in the function lagsarlm in the spdep 
package for a maximum likelihood way to estimate the spatial 
autoregressivemodel for continuous (normal) data. spdep has all kinds of 
ways to calculate the spatial weight matrices too.
Regards,
Eelke

Op 8/7/2012 5:46 PM, CARTIER, ADRIAN AW (AG/1000) schreef:
> Greetings:
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> I am a relatively new user to R. I was wondering if anyone is familiar with MATLAB's far_g() function.  If yes, is there an R equivalent to this?  I would like to have the ability to input as my observation vector continuous values. I noticed that there was something close in R, sar_probit_mcmc(), but I can only use a binary vector as my observation vector.
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> If my question sounds a bit confusing I am pasting below the MATLAB description of the function so you can see what it is that I am looking for.
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> function results =ar_g(y,W,ndraw,nomit,prior) % PURPOSE: Bayesian estimates for the 1st-order Spatial autoregressive model
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> %          y =ho*W*y + e,    e = N(0,sige*V),
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> %          V =iag(v1,v2,...vn), r/vi = ID chi(r)/r, r = Gamma(m,k)
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> %          sige =amma(nu,d0)
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> %          rho =niform(rmin,rmax), or rho = beta(a1,a2);
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> Thanks in advance,
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> ______________________________________
> Adrian Cartier, Ph.D. (LS3428)
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