Bayesian Analyses

Scott Pardo ()
Additional contact information
Scott Pardo: Ascensia Diabetes Care, Global Medical & Clinical Affairs

Chapter Chapter 12 in Statistical Analysis of Empirical Data, 2020, pp 161-167 from Springer

Abstract: Abstract Bayesian philosophy treats parameters as random variables; data are used to update the knowledge about the parameters’ distributions. The Bayesian might treat the parameters’ distributions as the uncertainty about the knowledge of the parameters; Bayes’ Theorem provides a means of incorporating prior knowledge about the uncertainty with current data.

Keywords: Bayes’ theorem; Conjugate pairs; Credible interval; Markov chain; Monte Carlo; MCMC (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-43328-4_12

Ordering information: This item can be ordered from
http://www.springer.com/9783030433284

DOI: 10.1007/978-3-030-43328-4_12

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().