Adjust least-squares standard errors for spatial correlation and serial correlation in panel data. (Stata and Matlab code here) (The technique is GMM, as outlined by Conley 2008). Code is described here (please cite Hsiang 2010 when using).
Partial-out two variables from a model and plot them with a single command. (Stata) Code here.
Generate and analyze random networks (Matlab) Poisson, Watts-Strogatz, generate overlapping stars, plotting, computing empirical connection density, clustering coeff. Code here.
Data visualization tools
Watercolor Regression (MATLAB) Display a smooth nonparametric distribution of the probability density for a nonparametric regression estimate. Code is here. Watercolor regression (described here) is a type of visually-weighted regression (described here). Citation: Hsiang (2012) "Visually-Weighted Regression" (here).
Visually-Weighted Regression (STATA & MATLAB) Use the color-saturation of a regression line to denote the statistical confidence in the regression line at each point. Code is here. Described here with several options demonstrated here and the "watercolor regression" option described here. Citation: Hsiang (2012) "Visually-Weighted Regression" (here).
Three-Dimensional Nonparametric Regression (MATLAB) Flexibly estimate means conditional on two variables with bootstrapped confidence intervals. Code is here.
Boxplot Regression (MATLAB) Discretize an independent variable and use boxplots as a nonparametric regression. Code is here.
Perhaps our best loved lab members...
Dell T620 Server. 24 CPU cores @ 2.4 GHz, 36 TB disk, 96 GB memory.
Dell T630 Server. 48 CPU cores @ 3.0 GHz, 128 TB disk space, 256 GB memory.
Dell T630 Server. 24 CPU cores @ 3.0 GHz, 1 TB SSD disk, 84 GB memory.
4 x Dell Blade servers at Berkeley HPC. 96 CPU cores @ 2.3 GHz, 512 GB memory.
Synology DS1815+ NAS w/ 2x DX513 expansions. 88 TB disk space.