A decision maker has to choose one of several random variables, with uncertainty known distributions. As a Bayesian she behaves as if she knew the distributions. In his paper we suggest an axiomatic derivation of these (subjective) distributions, which is much more economical than the derivations by de Finetti or Savage. They derive the whole joint distribution of all the available random variables.
|Date of creation:||Dec 2001|
|Date of revision:|
|Publication status:||Published in Theory and Decisions (2004), 56: 345-357|
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- David Schmeidler, 2000.
"Utility in Case-Based Decision Theory,"
00-06, Ohio State University, Department of Economics.
- Itzhak Gilboa & David Schmeidler, 2001.
"A Theory of Case-Based Decisions,"
- Gilboa,Itzhak & Schmeidler,David, 2001. "A Theory of Case-Based Decisions," Cambridge Books, Cambridge University Press, number 9780521802345, November.
- Gilboa,Itzhak & Schmeidler,David, 2001. "A Theory of Case-Based Decisions," Cambridge Books, Cambridge University Press, number 9780521003117, November.
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