Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/80205 
Erscheinungsjahr: 
2005
Schriftenreihe/Nr.: 
Working Paper No. 2006-05
Verlag: 
Brown University, Department of Economics, Providence, RI
Zusammenfassung: 
Recent work by Schennach(2005) has opened the way to a Bayesian treatment of quantile regression. Her method, called Bayesian exponentially tilted empirical likelihood (BETEL), provides a likelihood for data y subject only to a set of m moment conditions of the form Eg(y, θ) = 0 where θ is a k dimensional parameter of interest and k may be smaller, equal to or larger than m. The method may be thought of as construction of a likelihood supported on the n data points that is minimally informative, in the sense of maximum entropy, subject to the moment conditions. Specifically the probabilities {pi} attached to the n data points are chosen to solve
Dokumentart: 
Working Paper

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