dorsal/arxiv
View SchemaOn Consistent and Calibrated Inference about the Parameters of Sampling Distributions
| Authors | Tomaz Podobnik, Tomi Zivko |
|---|---|
| Categories | |
| ArXiv ID | physics/0508017 |
| URL | https://arxiv.org/abs/physics/0508017 |
Abstract
The theory of probability, based on very general rules referred to as the Cox-Polya-Jaynes Desiderata, can be used both as a theory of random mass phenomena and as a quantitative theory of plausible inference about the parameters of sampling distributions. The existing applications of the Desiderata must be extended in order to allow for consistent inferences in the limit of complete a priori ignorance about the values of the parameters. Since the limits of consistent quantitative inference from incomplete information can clearly be established, the developed theory is necessarily an effective one. It is interesting to note that when applying the Desiderata strictly, we find no contradictions between the so-called Bayesian and frequentist schools of inductive reasoning.
{
"annotation_id": "80bf40f9-bf53-4f9c-ad12-aac1327c7ed6",
"date_created": "2026-03-02T18:00:59.815000Z",
"date_modified": "2026-03-02T18:00:59.815000Z",
"file_hash": "216eb35e98f462171b7fdc47d663cffffbee049418db331199f028abc1f08abe",
"private": false,
"record": {
"abstract": "The theory of probability, based on very general rules referred to as the\nCox-Polya-Jaynes Desiderata, can be used both as a theory of random mass\nphenomena and as a quantitative theory of plausible inference about the\nparameters of sampling distributions. The existing applications of the\nDesiderata must be extended in order to allow for consistent inferences in the\nlimit of complete a priori ignorance about the values of the parameters. Since\nthe limits of consistent quantitative inference from incomplete information can\nclearly be established, the developed theory is necessarily an effective one.\nIt is interesting to note that when applying the Desiderata strictly, we find\nno contradictions between the so-called Bayesian and frequentist schools of\ninductive reasoning.",
"arxiv_id": "physics/0508017",
"authors": [
"Tomaz Podobnik",
"Tomi Zivko"
],
"categories": [
"physics.data-an",
"hep-ex"
],
"title": "On Consistent and Calibrated Inference about the Parameters of Sampling Distributions",
"url": "https://arxiv.org/abs/physics/0508017"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "3d8c166e-512c-4260-a888-0bf2dde199ca",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}