{
  "annotation_id": "ddbdb62d-9df8-4a5c-ba8c-5694f48e3319",
  "date_created": "2026-03-02T18:01:03.291000Z",
  "date_modified": "2026-03-02T18:01:03.291000Z",
  "file_hash": "7eddc870ef613972453096e12c1d075d718ba3377cf583306b8d59fc74cb78aa",
  "private": false,
  "record": {
    "abstract": "The aim of this paper, triggered by some discussions in the astrophysics\ncommunity raised by astro-ph/0508529, is to introduce the issue of `fits\u0027 from\na probabilistic perspective (also known as Bayesian), with special attention to\nthe construction of model that describes the `network of dependences\u0027 (a\nBayesian network) that connects experimental observations to model parameters\nand upon which the probabilistic inference relies. The particular case of\nlinear fit with errors on both axes and extra variance of the data points\naround the straight line (i.e. not accounted by the experimental errors) is\nshown in detail. Some questions related to the use of linear fit formulas to\nlog-linearized exponential and power laws are also sketched, as well as the\nissue of systematic errors.",
    "arxiv_id": "physics/0511182",
    "authors": [
      "G. D\u0027Agostini"
    ],
    "categories": [
      "physics.data-an",
      "astro-ph"
    ],
    "title": "Fits, and especially linear fits, with errors on both axes, extra   variance of the data points and other complications",
    "url": "https://arxiv.org/abs/physics/0511182"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "28713e77-33d3-419b-b587-10cbe5e657ff",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}