Robust nonparametric equivariant regression for functional data with responses missing at random

被引:1
|
作者
Fetitah, Omar [1 ]
Attouch, Mohammed Kadi [1 ]
Khardani, Salah [2 ]
Righi, Ali [1 ]
机构
[1] Univ Djillali Liabes Sidi Bel Abbes, Lab Stat Proc Stochast, Sidi Bel Abbes, Algeria
[2] Fac Sci Tunis El Manar, Lab Anal stochast & applicat LASA, Tunis El Manar, Tunisia
关键词
Robust regression; Missing at random; Scale parameter; Functional data analysis; Almost complete convergence; PREDICTION; ESTIMATOR;
D O I
10.1007/s00184-023-00898-1
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The paper deal with the robust equivariant nonparametric regression when the covariates are functional and the response variables are missing at random (MAR). Under some mild conditions, the almost complete convergence rate of the proposed estimators for both cases known and unknown scale parameter are established. Some simulations study are drawing, and real data analysis are given to illustrate the higher predictive performances of our proposed method.
引用
收藏
页码:899 / 929
页数:31
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