regClimateChem: An R Package for Data Driven Variable Selection Applied to Atmospheric Carbon Monoxide

Simonson et al. [2] refactored the MATLAB codebase, improving both code interpretability and generality and adding parallelization options. In this technical note, we present further updates to the codebase used in the atmospheric CO analysis from Buchholz et al. [1]. These updates stem from four primary objectives.

First, transfer the codebase into an R package that is available to researchers without a MATLAB license. Second, allow for a single climate index to appear in the model multiple times with different lag values. Third, implement an exhaustive variable selection algorithm.

Finally, improve upon the non-exhaustive variable selection algorithm implemented in the MATLAB code. These updates are discussed, and the accuracy and timing of the new variable selection algorithms are compared.