Bayesian quantile regression

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: cemmap working paper ; No. CWP05/06

Classification and Topics

• Classification: Wirtschaft
• Subject: Bayes-Statistik ; Regression ; Theorie

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Lancaster, Tony ; Jun, Sung Jae
• Event: Veröffentlichung
• (who): Centre for Microdata Methods and Practice (cemmap)
• (where): London
• (when): 2006

Further information

• DOI: doi:10.1920/wp.cem.2006.0506
• Handle: http://hdl.handle.net/10419/79283
• Last update: 10.03.2025, 11:45 AM CET