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On the estimation of conditional quantiles - lecture 2

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Virtualconference
Auteurs : Maume-Deschamps, Véronique (Auteur de la Conférence)
CIRM (Editeur )

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Résumé : Estimation of conditional quantiles is requiered for many purposes, in particular when the conditional mean is not suffisiant to describe the impact of covariates on the dependent variable. For example, one may estimate the quantile of one financial index (e.g. WisdomTree Japan Hedged Equity Fund) knowing financial indeces from other countries. It is also requiered to estimated conditional quantiles in Quantile Oriented Sensitivity Analysis (QOSA). QOSA indices are relevant in order to quantify uncertainty on quantiles, for example in insurance operational risk contexts. We shall present several view points on conditional quantile estimation: quantile regression and improvements, Kernel based estimation, random forest estimation. We shall focus on applications to QOSA.

Keywords : sensitivity analysis; uncertainty avantification

Codes MSC :
62-07 - Data analysis
62G20 - Nonparametric asymptotic efficiency

Informations sur la Rencontre

Nom de la rencontre : Jean-Morlet Chair 2020 - Research School: Quasi-Monte Carlo Methods and Applications / Chaire Jean-Morlet 2020 - Ecole: Méthode de quasi-Monte-Carlo et applications
Organisateurs de la rencontre : Rivat, Joël ; Thonhauser, Stefan ; Tichy, Robert
Dates : 02/11/2020 - 07/11/2020
Année de la rencontre : 2020
URL Congrès : https://www.chairejeanmorlet.com/2255.html

Données de citation

DOI : 10.24350/CIRM.V.19680303
Citer cette vidéo: Maume-Deschamps, Véronique (2020). On the estimation of conditional quantiles - lecture 2. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.19680303
URI : http://dx.doi.org/10.24350/CIRM.V.19680303

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