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Approximate Bayesian computation — Wikipedia (en)

Source: Wikipedia (en)
Original: https://en.wikipedia.org/wiki/Approximate_Bayesian_computation
License (as archived): CC-BY-SA-4.0
Archived: 2026-10-15T15:02:23.850Z
SHA-256 of the archived text: f368b98604cd24eb28fe432cfe3baa607e61ebf1df4afba2b97d31f63f325e94
Stable URL of this page: https://metraipolis.com/documento/dc_9bc66ea00bcb

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Approximate Bayesian computation — Wikipedia (en) — Wikipedia (en), https://en.wikipedia.org/wiki/Approximate_Bayesian_computation (CC-BY-SA-4.0); archived copy: https://metraipolis.com/documento/dc_9bc66ea00bcb (Metraipolis archive dc_9bc66ea00bcb, sha256 f368b98604cd24eb28fe432cfe3baa607e61ebf1df4afba2b97d31f63f325e94)

BibTeX

@misc{dc9bc66ea00bcb,
  title = {Approximate Bayesian computation — Wikipedia (en)},
  howpublished = {Wikipedia (en)},
  url = {https://en.wikipedia.org/wiki/Approximate_Bayesian_computation},
  note = {License CC-BY-SA-4.0; archived copy https://metraipolis.com/documento/dc_9bc66ea00bcb; sha256 f368b98604cd24eb28fe432cfe3baa607e61ebf1df4afba2b97d31f63f325e94},
  year = {2026}
}

Archived text

Reproduced under CC-BY-SA-4.0. Attribution: Wikipedia (en), https://en.wikipedia.org/wiki/Approximate_Bayesian_computation. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics that can be used to estimate the posterior distributions of model parameters. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences, e.g. in population genetics, ecology, epidemiology, systems biology, and in radio propagation.

Tema degli esploratori: statistica e scienza dei dati (deposito sistematico; categoria «Bayesian statistics»).
Fonte: Wikipedia in inglese, voce «Approximate Bayesian computation» — https://en.wikipedia.org/wiki/Approximate_Bayesian_computation
Wikidata Q21045424 (dati Wikidata in CC0 1.0) — https://www.wikidata.org/wiki/Q21045424
Autori: i contributori di Wikipedia (cronologia: https://en.wikipedia.org/wiki/Approximate_Bayesian_computation?action=history).
Licenza: Creative Commons Attribuzione-Condividi allo stesso modo 4.0 (CC BY-SA 4.0) — https://creativecommons.org/licenses/by-sa/4.0/. Il riuso richiede attribuzione e stessa licenza.
Estratto dell'introduzione non modificato nel contenuto; revisione 1374041215, consultata il 2026-10-15T14:06:05.841Z tramite l'API ufficiale di Wikipedia. Impronta SHA-256 dell'estratto: 1d9d90d7bb79ffa08cf1d0ab8816c69c2ade36c9448dd106805364500e3135d1