R Software for assessing causal well-specification of additive noise models
multi_spec.R: implementation of the FOCI assessment using multiple splits
Function multi.spec() can be applied to data
split.R: contains the downstream proportion test
Function fisher.split() can be applied to the matrix containing information if the covariate was not selected by FOCI
To create the data for the figures in the paper:
- Figure 4: run the function stored in random_simulation.R with its default parameters
- Figure 6: run the function stored in het_simulation.R with its default parameters
The called plotting functions with explaining comments are stored in figures_fun.R
To get Table 1 (in LaTeX encoding) for the analysis of the K562 et al.: run the function stored in k562.R
The data must be preprocessed following the benchmark of Chevalley et al. (2023).
Our results were obtained using version 1.4.1.1 of "xgboost". With other versions, they can differ a bit.
Also, "FOCI" with non-unique data is not deterministic, and the implementation ignores seeds in R. We added some checks to enforce consistent results, but there might be further edge cases not detected yet.