Software
An overview of my software development projects.
I enjoy using and contributing to open-source scientific software. I’ve co-developed the following software packages in R and python.
maars
An R implementation of the series of papers (Buja, Brown, Berk, et al. 2019) and (Buja, Brown, Kuchibhotla, et al. 2019) based on a tidy grammar. This is joint work with Riccardo Fogliato and Arun Kumar Kuchibhotla.
iRF
A python package to implement the iterative Random Forest (iRF) family of algorithms from (Basu et al. 2018). This implementation is a joint effort of several people from the Yu Group at UC Berkeley. See here for the complete list of developers.
References
Basu, Sumanta, Karl Kumbier, James B. Brown, and Bin Yu. 2018. “Iterative Random Forests to Discover Predictive and Stable High-Order Interactions.” Proceedings of the National Academy of Sciences 115 (8): 1943–48. https://doi.org/10.1073/pnas.1711236115.
Buja, Andreas, Lawrence Brown, Richard Berk, Edward George, Emil Pitkin, Mikhail Traskin, Kai Zhang, and Linda Zhao. 2019. “Models as Approximations I: Consequences Illustrated with Linear Regression.” Statist. Sci. 34 (4): 523–44. https://doi.org/10.1214/18-STS693.
Buja, Andreas, Lawrence Brown, Arun Kumar Kuchibhotla, Richard Berk, Edward George, and Linda Zhao. 2019. “Models as Approximations II: A Model-Free Theory of Parametric Regression.” Statist. Sci. 34 (4): 545–65. https://doi.org/10.1214/18-STS694.