{
  "abstract": "Vogels et al. (2024) presented an empirical comparison of Bayesian methods for structure learning in undirected Gaussian graphical models. The method implemented in the R package BGGM was run with equal prior probabilities for a null, negative, and positive partial correlation, implying a prior inclusion probability (equivalent to a prior graph density) of 2/3. The other Bayesian methods in the comparison used a prior graph density of 0.2 however. The data-generating densities ranged from 0.01 to 0.1. This resulted in a substantial overestimation of the inclusion probabilities of absent edges by BGGM. For a fair comparison of the performance of the different methods, I repeated the simulation using a prior inclusion probability of 0.2 using BGGM. In this case, the performance of BGGM is comparable with the other Bayesian methods.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.31969",
  "author_total": 1,
  "authors": [
    {
      "name": "Joris Mulder"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9szqd9sae8sgd.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.31969",
  "fulltext_url": null,
  "id": "9szqd9sae8sgd",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.31969",
  "language": null,
  "licence": "CC-BY-SA-4.0",
  "licence_label": "CC BY-SA 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by-sa/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "stat.ME"
    ],
    [
      "openalex",
      "2613|Statistical Methods and Inference"
    ]
  ],
  "openalex": "W7214703711",
  "pdf_url": "https://arxiv.org/pdf/2609.31969",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-25",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9szqd9sae8sgd.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:26Z",
      "native_id": "2609.31969",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.31969"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.ME",
      "subfield": "statistics"
    }
  ],
  "title": "Comment on Vogels et al.'s (2024) \"Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison\": An updated performance check using BGGM",
  "title_text": "Comment on Vogels et al.'s (2024) \"Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison\": An updated performance check using BGGM",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:26Z",
  "url": "https://research.draconitic.com/paper/9szqd9sae8sgd",
  "venue": "arXiv",
  "versions": []
}