{
  "abstract": "Mean-tilted intervals (MTIs) provide a fixed-content family of interval targets indexed by retained-mean balance. This paper develops generalized-Bayes computation for using those targets in regression and time-varying endpoint models after content and tilt have been specified. The update combines a prior with an exponentiated residual-product check loss, yielding uncertainty summaries for endpoint functions rather than a response-distribution model. A pseudo-asymmetric-Laplace normal-exponential representation gives generalized-inverse-Gaussian latent-scale updates and Gaussian conditional updates for one root when the other is fixed. The same representation gives deterministic ECM equations for generalized-posterior modes. We present ridge endpoint regression, a conditionally Gaussian shrinkage construction for the zero-tilt case, deterministic fixed-feature readouts, and dynamic linear endpoint states updated by alternating forward-filtering backward-sampling steps. These methods extend the MTI target from iid intervals to regression and dynamic settings; tolerance certification and response prediction require separate calibration or response models.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.13960",
  "author_total": 3,
  "authors": [
    {
      "name": "Antonio De Leon"
    },
    {
      "name": "Raquel Prado"
    },
    {
      "name": "Bruno Sansó"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1sdvy9f7yk2py.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.13960",
  "fulltext_url": null,
  "id": "1sdvy9f7yk2py",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.13960",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "stat.ME"
    ],
    [
      "openalex",
      "2613|Statistical Methods and Bayesian Inference"
    ]
  ],
  "openalex": "W7221753624",
  "pdf_url": "https://arxiv.org/pdf/2610.13960",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-01",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/1sdvy9f7yk2py.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:26Z",
      "native_id": "2610.13960",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.13960"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.ME",
      "subfield": "statistics"
    }
  ],
  "title": "Mean-Tilted Intervals: Regression and Dynamic Models",
  "title_text": "Mean-Tilted Intervals: Regression and Dynamic Models",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:26Z",
  "url": "https://research.draconitic.com/paper/1sdvy9f7yk2py",
  "venue": "arXiv",
  "versions": []
}