STRONG CONSISTENCY RATE OF THE CONDITIONAL QUANTILE ESTIMATOR WITH DATA MISSING AT RANDOM

被引：0

作者：

Bourouba, Assia ^{[1
]}

Hamidi, Nesrine ^{[2
]}

Mechab, Boubaker ^{[2
]}

Litimein, Ouahiba ^{[2
]}

机构：

[1] Univ Djillali Liabes Sidi Bel Abbes, Dept Probabil & Stat, Biomath Lab, Sidi Bel Abbes 22000, Algeria

[2] Univ Djillali Liabes Sidi Bel Abbes, Dept Probabil & Stat, Lab Stat & Stochast Proc, Sidi Bel Abbes 22000, Algeria

来源：

JOURNAL OF SCIENCE AND ARTS | 2022年 / 04期

关键词：

conditional quantile; FDA; kernel estimator; missing at random; strong mixing; NONPARAMETRIC-ESTIMATION; REGRESSION;

D O I：

10.46939/J.Sci.Arts-22.4-a03

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

In the case of response missing at random conditioned by a functional explanatory variable, this research investigates non parametric estimate of the conditional quantile using the kernel approach. Under an a-mixing assumption and properties of the small ball, we establish the uniform almost complete convergence (with rate) of the proposed estimator.

引用

页码：811 / 820

页数：10

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