I am trying to run
netlogit on a network of about 60,000 nodes, and I would like to know if the SNA package's functions are designed to support such large operations. I know, for instance, that with RSiena we are not supposed to go further than a few hundred nodes for the algorithms to converge in a reasonable time. But is this the case with SNA's regression models as well?
My initial experience is negative: When I run the commands on my network, the R process expands in memory until it fills both the live memory and the virtual memory and then it crashes (even with one repetition). Is this a matter throwing more resource at R, and is there a good way to calculate how much? Or are the current MRQAP algorithms simply not adapted to such networks? Any resources that can help determine the requirements?