Thanks Corey. Yeah, what you mentioned is indeed the problem. However, does INLA can deal with the problem of many "zero" values if a count data model is assumed?
>You need to be careful with the incidence data if the Gaussian model isn't appropriate, I assume that many >counties have very low prevalence, so a count data model may be more appropriate. I would check out INLA, >it will do Bayesian models over space and time, there are some tutorials/examples here: http://www.r->inla.org/examples >My 2 cents >Corey -- View this message in context: http://r-sig-geo.2731867.n2.nabble.com/spatio-temporal-simultaneous-autoregression-model-tp7586871p7586887.html Sent from the R-sig-geo mailing list archive at Nabble.com. _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
