Dear fellow R users, I am fairly new to spatial models. I have been using "spdep" package to model the spatial correlation between my data points. I have used "dnearneigh" and "knearneigh" functions to get the neighborhood list. I don't have a problem running the functions when the data is small. My problem is the data set that I will eventually be working on is fairly large (more than 50,000 points). Thus I face with memory problem. Is there a way to speed up this process, like maybe creating the neighborhoods in clusters and combine them later to get large weight matrix for the "spautolm" function? any idea, suggestion is appreciated. Thanks and Regards
dealing with large spatial data
1 message · Ozlem Yanmaz