Noninformative priors for inferences in exponential regression models
Publication
, Journal Article
Ye, K; Berger, JO
Published in: Biometrika
September 1, 1991
SUMMARY: In the exponential regression model, inference concerning the regression parameter is notoriously difficult, even when using the Bayesian noninformative prior approach. The reference prior approach (Bernardo, 1979; Berger & Bernardo, 1989) is considered, and argued to yield very satisfactory inferences. Estimation and credible sets are considered in a specific example. © 1991 Biometrika Trust.
Duke Scholars
Published In
Biometrika
DOI
ISSN
0006-3444
Publication Date
September 1, 1991
Volume
78
Issue
3
Start / End Page
645 / 656
Related Subject Headings
- Statistics & Probability
- 1403 Econometrics
- 0104 Statistics
- 0103 Numerical and Computational Mathematics
Citation
APA
Chicago
ICMJE
MLA
NLM
Ye, K., & Berger, J. O. (1991). Noninformative priors for inferences in exponential regression models. Biometrika, 78(3), 645–656. https://doi.org/10.1093/biomet/78.3.645
Ye, K., and J. O. Berger. “Noninformative priors for inferences in exponential regression models.” Biometrika 78, no. 3 (September 1, 1991): 645–56. https://doi.org/10.1093/biomet/78.3.645.
Ye K, Berger JO. Noninformative priors for inferences in exponential regression models. Biometrika. 1991 Sep 1;78(3):645–56.
Ye, K., and J. O. Berger. “Noninformative priors for inferences in exponential regression models.” Biometrika, vol. 78, no. 3, Sept. 1991, pp. 645–56. Scopus, doi:10.1093/biomet/78.3.645.
Ye K, Berger JO. Noninformative priors for inferences in exponential regression models. Biometrika. 1991 Sep 1;78(3):645–656.
Published In
Biometrika
DOI
ISSN
0006-3444
Publication Date
September 1, 1991
Volume
78
Issue
3
Start / End Page
645 / 656
Related Subject Headings
- Statistics & Probability
- 1403 Econometrics
- 0104 Statistics
- 0103 Numerical and Computational Mathematics