Spatial Autocorrelation Functions

Mar 9, 2018 - 19 minutes
I looked into using spatial autocorrelation functions in my dissertation to characterize the ``scale” at which processes operate electorally. I did an analysis of presidential vote by county, trying to identify where, exactly, clusters of votes tend to become decorrelated. The typical diameter at which the so-called “spatial autocorrelation function” goes to zero denotes how wide a typical spatial cluster might be, and the partial spatial autocorrelation function gives an anticipated order at which spatial autocorrelation may hold. Read more ...

Reverse-PCA for making sense of the typical structure in multivariate models

Feb 28, 2018 - 3 minutes
I don’t really have a good idea for what many places in the UK are like, nor for what the structure of some of this data is when considering its joint structure. So, while my model fits quite well and yields some interesting results, I’m a bit limited because I don’t really know what a place like Barrow-in-Furness is like, without looking into it. In general, it’s more difficult to get a sense of what the model’s telling me from the conditional estimates because I don’t really have a sense of the joint picture: I don’t really intuit how they covary across places, like I might in US counties or states. Read more ...