A Bayesian Look at Nonidentifiability: A Simple Example

Sergio Wechsler, Rafael Izbicki and Luís Gustavo Esteves

The American Statistician, 2013, vol. 67, issue 2, 90-93

Abstract: This article discusses the concept of identifiability in simple probability calculus. Emphasis is given to Bayesian solutions. In particular, we compare Bayes and maximum likelihood estimators. We advocate adoption of informative prior probabilities for the Bayesian operation in place of diffuse or reference priors. We also discuss the concept of identifying functions.

Date: 2013
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00031305.2013.778787 (text/html)
Access to full text is restricted to subscribers.

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:taf:amstat:v:67:y:2013:i:2:p:90-93

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UTAS20

DOI: 10.1080/00031305.2013.778787

Access Statistics for this article

The American Statistician is currently edited by Eric Sampson

More articles in The American Statistician from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().