All data (in .csv and .rds format), figures (in .pdf format) and code (in the R and Julia languages), for the paper Shapley value confidence intervals for attributing variance explained by Daniel Fryer, Inga Strumke and Hien Nguyen.
The Monte Carlo simulation results and Shapley values were calculated in Julia, because this worked out to be much faster than doing it in R, even when we tried with parallel processing, and even when we used C via Rcpp.
The figures (including Monte Carlo and benchmark figures), and some exploratory analysis of the real estate data, were produced in R. For the real estate data, Shapley values with asymptotic and boostrap confidence intervals were produced in Julia.
Enjoy! Feel free to contact Daniel Fryer if you have any questions or concerns.