Semiparametric conditional quantile estimation through copula-based multivariate models
Year of publication: |
2015
|
---|---|
Authors: | Noh, Hohsuk ; El Ghouch, Anouar ; Van Keilegom, Ingrid |
Published in: |
Journal of business & economic statistics : JBES ; a publication of the American Statistical Association. - Alexandria, Va. : American Statistical Association, ISSN 0735-0015, ZDB-ID 876122-X. - Vol. 33.2015, 2, p. 167-178
|
Subject: | Check function | Dependence modeling | Markov process | Pseudo-log-likelihood | Vine copulas | Multivariate Verteilung | Multivariate distribution | Markov-Kette | Markov chain | Nichtparametrisches Verfahren | Nonparametric statistics | Schätztheorie | Estimation theory | Multivariate Analyse | Multivariate analysis | Zeitreihenanalyse | Time series analysis | Schätzung | Estimation |
-
The effect of dependence on European market risk : a nonparametric time varying approach
Ascorbebeitia, Jone, (2022)
-
Nonparametric forecasting of multivariate probability density functions
Guégan, Dominique, (2018)
-
Efficient Estimation of Multivariate Semi-nonparametric GARCH Filtered Copula Models
Chen, Xiaohong, (2019)
- More ...
-
Empirical likelihood confidence intervals for dependent duration data
El Ghouch, Anouar, (2011)
-
On an extension of the promotion time cure model
Portier, François, (2018)
-
Linear censored quantile regression : a novel minimum-distance approach
De Backer, Mickaël, (2018)
- More ...