Regression model for surrogate data in high dimensional statistics

DOI10.1080/03610926.2019.1586940OpenAlexW2961093137MaRDI QIDQ5077253

Firas Ibrahim, Ali Hajj Hassan, Mustapha Rachdi, Jacques Demongeot

Publication date: 18 May 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2019.1586940

zbMATH Keywords

surrogate dataregression estimationsmall ball probabilitymean square convergencefunctional data analysis (FDA)almost-complete convergenceclassical kernel estimatork nearest neighbors (kNN)

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35) Nonparametric estimation (62G05) Order statistics; empirical distribution functions (62G30) Statistics of extreme values; tail inference (62G32) Statistics (62-XX)

Related Items

k‐Nearest neighbors local linear regression for functional and missing data at random ⋮ Estimation in nonparametric functional-on-functional models with surrogate responses ⋮ FDA: theoretical and practical efficiency of the local linear estimation based on the kNN smoothing of the conditional distribution when there are missing data ⋮ Unnamed Item

Uses Software

• fda (R)

Cites Work

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