Modeling the Learning from Repeated Samples: A Generalized Cross Entropy Approach
In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information and learning from repeated samples. The basis for this method has its roots in information theory and builds on the classical maximum entropy work of Janes (1957). We illustrate the use of this approach, describe how to impose restrictions on the estimator, and how to examine the sensitivity of ME estimates to the parameter and error bounds. Our objective is to show how empirical measures of the value of information for microeconomic models can be estimated in the maximum entropy view.
|Date of creation:||2003|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.wiwi.hu-berlin.de/
More information through EDIRC
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.:
- Judge, G. G. & Hill, R. Carter & Bock, M. E., 1990. "An adaptive empirical Bayes estimator of the multivariate normal mean under quadratic loss," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 189-213.
- Golan, Amos & Judge, G. & Miller, D., 1997. "The Maximum Entropy Approach to Estimation and Inference: An Overview," Staff General Research Papers 1327, Iowa State University, Department of Economics.
- Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
- Miller, D. & Golan, Amos & Judge, G., 1998. "Information Recovery in Simultaneous Equation Statistical Models," Staff General Research Papers 1319, Iowa State University, Department of Economics.
When requesting a correction, please mention this item's handle: RePEc:zbw:sfb373:200329. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - German National Library of Economics)
If references are entirely missing, you can add them using this form.