Uncertainty in prior elicitations: a nonparametric approach

By Jeremy E. Oakley, Anthony OʼHagan. 2007

95 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/53453b5f1e0af433ff0c71a4a6d68d429810c1f2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. S. Thompson
2. Rebecca M. Turner
3. Joseph B. Kadane
4. Paul H. Garthwaite
5. David J. Spiegelhalter
6. Gordon C. S. Smith
7. Anthony OʼHagan
8. Karen E. Willcox

In Computational Theory and Mathematics

1. Paul H. Garthwaite
2. Joseph B. Kadane
3. S. Thompson
4. Gordon C. S. Smith
5. Rebecca M. Turner
6. David J. Spiegelhalter
7. Anthony OʼHagan
8. Luigi Cavaleri

In Statistical and Nonlinear Physics

1. Paul H. Garthwaite
2. Joseph B. Kadane
3. S. Thompson
4. Gordon C. S. Smith
5. Rebecca M. Turner
6. David J. Spiegelhalter
7. Anthony OʼHagan

Citations in the corpus

• Statistical Methods for Eliciting Probability Distributions (2005, methodology): “A more recent approach is that of Oakley and O’Hagan (2002), which adopts the framework of modern Bayesian nonparametrics.”
• Bias modelling in evidence synthesis (2009, methodology): “A full Bayesian analysis could also incorporate biases that are elicited through a flexible elicitation procedure (Oakley and O’Hagan, 2007).”