Supplementary data and analysis code for "Hierarchical Bayesian analysis of the radial acceleration relation scatter: a causal diagram approach to error calibration and intrinsic diversity,"
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| Format: | Recurso digital |
| Language: | English |
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Zenodo
2026
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| _version_ | 1866902227110592512 |
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| author | tanigawa, masato |
| author_facet | tanigawa, masato |
| contents | <p>This archive contains Python scripts and intermediate results for a hierarchical Bayesian analysis of the radial acceleration relation (RAR) scatter in 171 SPARC galaxies. The analysis uses a directed acyclic graph (DAG) to encode causal assumptions, hierarchical Bayesian inference to simultaneously estimate intrinsic inter-galaxy scatter (sigma_halo) and error scale factors (alpha_D, alpha_Inc), and do-calculus to decompose the scatter into causal components.</p> <p>Contents:</p> <ul> <li>scripts/ : 9 Python scripts (numbered 00-08) that reproduce all results and figures</li> <li>results/ : 13 CSV files and 2 NPZ files containing MCMC posterior samples and summary statistics</li> <li>src/ : Data loading module for the SPARC database</li> <li>README.md : Detailed documentation of all files, dependencies, and reproduction instructions</li> </ul> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19481106 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Supplementary data and analysis code for "Hierarchical Bayesian analysis of the radial acceleration relation scatter: a causal diagram approach to error calibration and intrinsic diversity," tanigawa, masato radial acceleration relation hierarchical Bayesian inference directed acyclic graph causal inference SPARC <p>This archive contains Python scripts and intermediate results for a hierarchical Bayesian analysis of the radial acceleration relation (RAR) scatter in 171 SPARC galaxies. The analysis uses a directed acyclic graph (DAG) to encode causal assumptions, hierarchical Bayesian inference to simultaneously estimate intrinsic inter-galaxy scatter (sigma_halo) and error scale factors (alpha_D, alpha_Inc), and do-calculus to decompose the scatter into causal components.</p> <p>Contents:</p> <ul> <li>scripts/ : 9 Python scripts (numbered 00-08) that reproduce all results and figures</li> <li>results/ : 13 CSV files and 2 NPZ files containing MCMC posterior samples and summary statistics</li> <li>src/ : Data loading module for the SPARC database</li> <li>README.md : Detailed documentation of all files, dependencies, and reproduction instructions</li> </ul> |
| title | Supplementary data and analysis code for "Hierarchical Bayesian analysis of the radial acceleration relation scatter: a causal diagram approach to error calibration and intrinsic diversity," |
| topic | radial acceleration relation hierarchical Bayesian inference directed acyclic graph causal inference SPARC |
| url | https://doi.org/10.5281/zenodo.19481106 |