{
  "annotation_id": "9e295823-356f-4f1b-9f08-a013985b4bd3",
  "date_created": "2026-03-02T18:00:35.802000Z",
  "date_modified": "2026-03-02T18:00:35.802000Z",
  "file_hash": "9d1569c3b16f45e325c07d312d2aecac56ba850d04465efe448113e069b21fd2",
  "private": false,
  "record": {
    "abstract": "We present alphaPDE, a new multivariate analysis technique for parameter\nestimation. The method is based on a direct construction of joint probability\ndensities of known variables and the parameters to be estimated. We show how\nposterior densities and best-value estimates are then obtained for the\nparameters of interest by a straightforward manipulation of these densities.\nThe method is essentially non-parametric and allows for an intuitive graphical\ninterpretation. We illustrate the method by outlining how it can be used to\nestimate the mass of the top quark, and we explain how the method is applied to\nan ensemble of events containing background.",
    "arxiv_id": "physics/0108002",
    "authors": [
      "B. Knuteson",
      "H. Miettinen",
      "L. Holmstrom"
    ],
    "categories": [
      "physics.data-an",
      "hep-ex"
    ],
    "doi": "10.1016/S0010-4655(02)00279-5",
    "journal_ref": "Comput.Phys.Commun. 145 (2002) 351-356",
    "title": "alphaPDE: A New Multivariate Technique for Parameter Estimation",
    "url": "https://arxiv.org/abs/physics/0108002"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "14f7711e-6a5a-4d54-b0f7-b9c8a6f57767",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}