Instructions for Reproducible Materials

Organization

• Bash script (batch.sh): automate the execution of all numerical simulation studies
• R scripts (.R): implement baseline methods, evaluation metrics, simulation studies, real-data analysis of the congressional voting dataset
• Data files (.csv): for real-world data analysis. It is available at Dropbox.

File Descriptions

Main R scripts

• simu_degree.R — empirical sample complexity analysis with respect to the degree.
• simu_beta.R — empirical sample complexity analysis with respect to the maximum signal.
• simu_high.R — experiments for high-dimensional cases.
• simu_p.R — empirical sample complexity analysis with respect to the dimension.
• simu_ws.R — empirical sample complexity analysis with respect to the weakest signal.
• DataAnalysis.R — real-data analysis: data cleaning, estimation of the graphical structure among senators, and visualization.

Utility R scripts (automatically used by the main scripts)

• simulation_main.R — runs one method on a given simulated dataset.
• method_implementation.R — implementations of baseline methods (RPLE, RISE, logRISE, ELASSO, RLRF).
• evaluation.R — evaluation metrics (e.g., Frobenius norm, true positive rate).

Reproducing Results

The scripts reproduce the results presented in the paper as follows:

• Figure 1 and Table S1 → simu_degree.R
• Figure 2 and Figure S1 → simu_beta.R
• Figure 3 and Figure S2 → simu_high.R
• Figure S3 → simu_p.R
• Figure S4 → simu_ws.R
• Figure 4 → DataAnalysis.R

The simplest procedure on reproduction:

1. Use the provided bash scripts (batch.sh) to execute the full set of simulation automatically.
2. Run DataAnalysis.R to reproduce the real-data analysis (Figure 4).