Arbeitspapier
Bayesian quantile regression
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.
- Sprache
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Englisch
- Erschienen in
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Series: cemmap working paper ; No. CWP05/06
- Klassifikation
-
Wirtschaft
- Thema
-
Bayes-Statistik
Regression
Theorie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Lancaster, Tony
Jun, Sung Jae
- Ereignis
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Veröffentlichung
- (wer)
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Centre for Microdata Methods and Practice (cemmap)
- (wo)
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London
- (wann)
-
2006
- DOI
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doi:10.1920/wp.cem.2006.0506
- Handle
- Letzte Aktualisierung
-
20.09.2024, 08:21 MESZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Lancaster, Tony
- Jun, Sung Jae
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2006