Model uncertainty
Publication
, Journal Article
Clyde, M; George, EI
Published in: Statistical Science
February 1, 2004
The evolution of Bayesian approaches for model uncertainty over the past decade has been remarkable. Catalyzed by advances in methods and technology for posterior computation, the scope of these methods has widened substantially. Major thrusts of these developments have included new methods for semiautomatic prior specification and posterior exploration. To illustrate key aspects of this evolution, the highlights of some of these developments are described.
Duke Scholars
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Published In
Statistical Science
DOI
ISSN
0883-4237
Publication Date
February 1, 2004
Volume
19
Issue
1
Start / End Page
81 / 94
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 0104 Statistics
Citation
APA
Chicago
ICMJE
MLA
NLM
Clyde, M., & George, E. I. (2004). Model uncertainty. Statistical Science, 19(1), 81–94. https://doi.org/10.1214/088342304000000035
Clyde, M., and E. I. George. “Model uncertainty.” Statistical Science 19, no. 1 (February 1, 2004): 81–94. https://doi.org/10.1214/088342304000000035.
Clyde M, George EI. Model uncertainty. Statistical Science. 2004 Feb 1;19(1):81–94.
Clyde, M., and E. I. George. “Model uncertainty.” Statistical Science, vol. 19, no. 1, Feb. 2004, pp. 81–94. Scopus, doi:10.1214/088342304000000035.
Clyde M, George EI. Model uncertainty. Statistical Science. 2004 Feb 1;19(1):81–94.
Published In
Statistical Science
DOI
ISSN
0883-4237
Publication Date
February 1, 2004
Volume
19
Issue
1
Start / End Page
81 / 94
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 0104 Statistics