Unsupervised learning for time series data: Singular spectrum versus principal components analysis

Recently, I was working with a colleague on a project involving time series observations of neighborhoods in Los Angeles. We wanted to see if there were patterns in the time series data that described how similar neighborhoods evolved in time. For multivariate data, this is a great application for unsupervised …

Teaching the Q Method in a class on urban sustainability

The Q Method is a mixed method that combines a survey of individuals with factor analysis to determine what distinct perspectives are embedded in a population. In a class on urban sustainability, I demonstrated how this method can be used to reveal students' diverse perspectives on issues about which we assume they mostly agree.

Diagnostics for fixed effects panel models in R

In working with linear fixed-effects panel models, I discovered that I had to develop goodness-of-fit tests and diagnostics on my own, as the libraries for working with these kinds of models haven't progressed that far yet.