[R-sig-Geo] SAR Poisson GLM model
clement.gorin at univ-st-etienne.fr
Mon Feb 1 10:36:40 CET 2016
I am estimating a gravity model of migration on cross-sectional data. The Moran I statistic indicates a positive and significant spatial autocorrelation in the residuals of the a-spatail model, and the Lagrange Multiplier test points to the Spatial Autoregressive (SAR) model as the preferred specification. While I have no issue fitting a linear SAR (Le Sage and Pace 2008) to my data, it does not accommodate the very large number of zeroes (> 90%) in my dependent variable. This clearly point to a Poisson process (Santos Silva and Tenreyro 2006).
In short, I am having trouble running the SAR Poisson GLM. I had two questions:
(1) Is there a method to run a SAR Poisson GLM in R? (I searched a lot before posting here)
(2) If answer to (1) is no, I should at least use a spatially filtered Poisson GLM. Yet, both SptatialFiltering() and ME() crash even using a very simple connectivity structure (symmetric knn = 5). I mean that it did not give any message error but RStudio simply "lost the connection with the R session". I suspect this is due to the large number of observation (278 784). Do you have tips to increase computational efficiency?
PhD student, GATE LSE
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