Conditional Quantile Sequential Estimation for Stochastic Codes

被引：0
作者：
Tatiana Labopin-Richard
Fabrice Gamboa
Aurélien Garivier
Jérôme Stenger
机构：
[1] Université Paul Sabatier,Institut de Mathématique de Toulouse
[2] École Normale Supérieure de Lyon,Unité de Mathématiques Pures et Appliquées, Laboratoire de l’Informatique du Parallélisme
[3] Université de Lyon,undefined
[4] EDF R&D,undefined
来源：
Journal of Statistical Theory and Practice | 2019年 / 13卷
关键词：
Stochastic code; Conditional quantile; Robbins–Monro stochastic algorithm; -Nearest neighbors method; 62L12; 62L20; 62G32;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We propose and analyze an algorithm for the sequential estimation of a conditional quantile in the context of real stochastic codes with vector-valued inputs. Our algorithm is based on k-nearest neighbors smoothing within a Robbins–Monro estimator. We discuss the convergence of the algorithm under some conditions on the stochastic code. We provide non-asymptotic rates of convergence of the mean squared error, and we discuss the tuning of the algorithm’s parameters.
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