Staff View: Bayesian inference on a proportion believed to be a simple fraction.

Bayesian inference on a proportion believed to be a simple fraction.

Bibliographic Details
Main Author:	Frey, Jesse.
Format:	Villanova Faculty Authorship
Language:	English
Published:	2007
Online Access:	http://ezproxy.villanova.edu/login?url=https://digital.library.villanova.edu/Item/vudl:176355

Main Author:

Frey, Jesse.

Format:

Villanova Faculty Authorship

Language:

English

Published:

2007

Online Access:

http://ezproxy.villanova.edu/login?url=https://digital.library.villanova.edu/Item/vudl:176355

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spelling	Bayesian inference on a proportion believed to be a simple fraction. Frey, Jesse. This article considers the problem of making inference on a proportion when there is reason to believe that the proportion is a simple fraction. By a simple fraction we mean a fraction that, when put in lowest terms, has a small denominator. After discussing the history of Bayesian inference on a proportion, we propose a class of otherwise noninformative priors that incorporates the idea that the proportion is likely to be a simple fraction, and we explore the impact of the choice of parameter. We propose the posterior mode as a point estimator, and we study the behavior of this estimator both asymptotically and for small sample sizes. We illustrate our approach by applying it both to the famous problem of estimating the probability that the sun will rise again tomorrow and to examples from the scientific work of the Augustinian friar Gregor Mendel. 2007 Villanova Faculty Authorship vudl:176355 The American Statistician 61(3), August 2007, 201-206. en
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dc.description_txt_mv	This article considers the problem of making inference on a proportion when there is reason to believe that the proportion is a simple fraction. By a simple fraction we mean a fraction that, when put in lowest terms, has a small denominator. After discussing the history of Bayesian inference on a proportion, we propose a class of otherwise noninformative priors that incorporates the idea that the proportion is likely to be a simple fraction, and we explore the impact of the choice of parameter. We propose the posterior mode as a point estimator, and we study the behavior of this estimator both asymptotically and for small sample sizes. We illustrate our approach by applying it both to the famous problem of estimating the probability that the sun will rise again tomorrow and to examples from the scientific work of the Augustinian friar Gregor Mendel.
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title	Bayesian inference on a proportion believed to be a simple fraction.
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Bayesian inference on a proportion believed to be a simple fraction.
Frey, Jesse.
This article considers the problem of making inference on a proportion when there is reason to believe that the proportion is a simple fraction. By a simple fraction we mean a fraction that, when put in lowest terms, has a small denominator. After discussing the history of Bayesian inference on a proportion, we propose a class of otherwise noninformative priors that incorporates the idea that the proportion is likely to be a simple fraction, and we explore the impact of the choice of parameter. We propose the posterior mode as a point estimator, and we study the behavior of this estimator both asymptotically and for small sample sizes. We illustrate our approach by applying it both to the famous problem of estimating the probability that the sun will rise again tomorrow and to examples from the scientific work of the Augustinian friar Gregor Mendel.
2007
Villanova Faculty Authorship
vudl:176355
The American Statistician 61(3), August 2007, 201-206.
en

dc.title_txt_mv

Bayesian inference on a proportion believed to be a simple fraction.

dc.creator_txt_mv

Frey, Jesse.

dc.description_txt_mv

This article considers the problem of making inference on a proportion when there is reason to believe that the proportion is a simple fraction. By a simple fraction we mean a fraction that, when put in lowest terms, has a small denominator. After discussing the history of Bayesian inference on a proportion, we propose a class of otherwise noninformative priors that incorporates the idea that the proportion is likely to be a simple fraction, and we explore the impact of the choice of parameter. We propose the posterior mode as a point estimator, and we study the behavior of this estimator both asymptotically and for small sample sizes. We illustrate our approach by applying it both to the famous problem of estimating the probability that the sun will rise again tomorrow and to examples from the scientific work of the Augustinian friar Gregor Mendel.

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Bayesian inference on a proportion believed to be a simple fraction.

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Bayesian inference on a proportion believed to be a simple fraction.

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subpages

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Bayesian inference on a proportion believed to be a simple fraction.

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