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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.

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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

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ICMJE
MLA
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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