All linear regression fits were performed using the nonparametric Theil-Sen estimator for slopes, as implemented in the Python library SciPy. The use of a Theil-Sen estimator is important because rather than attempting to minimize the sum of squared residuals -a framework that also requires that the residuals have constant variance and be normally distributed -it simply finds the median slope among all pairs of points in the data. This methodology enables the Theil-Sen estimator to be robust to outliers. The 95% confidence intervals for the slope estimates were computed using Sen's method.