Asymptotic Normality of Single Functional Index Quantile Regression for Functional Data with Missing Data at Random Cover Image

Asymptotyczna normalność regresji kwantylowej pojedynczego wskaźnika funkcyjnego dla danych funkcjonalnych z losowymi brakującymi danymi
Asymptotic Normality of Single Functional Index Quantile Regression for Functional Data with Missing Data at Random

Author(s): Anis Allal, Nadia Kadiri, Abbes Rabhi
Subject(s): Socio-Economic Research
Published by: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Keywords: asymptotic normality; functional data analysis; functional single-index process; missing at random; nonparametric estimation; small ball probability

Summary/Abstract: This work addresses the problem of the nonparametric estimation of the regression function, namely the conditional distribution and the conditional quantile in the single functional index model (SFIM) under the independent and identically distributed condition with randomly missing data. The main result of this study was the establishment of the asymptotic properties of the estimator, such as the almost complete convergence rates. Moreover, the asymptotic normality of the constructs was obtained under certain mild conditions. Lastly, the authors discussed how to apply the result to construct confidence intervals.

  • Issue Year: 28/2024
  • Issue No: 1
  • Page Range: 26-38
  • Page Count: 13
  • Language: English
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