Some Asymptotic Properties of Conditional Density Function for Functional Data Under Random Censorship

被引：0

作者：

Akkal, Fatima ^{[1
]}

Rabhi, Abbes ^{[2
]}

Keddani, Latifa ^{[3
]}

机构：

[1] Univ Djillali LIABES Sidi Bel Abbes, Stat & Stochast Proc Lab, POB 89, Sidi Bel Abbes 22000, Algeria

[2] Univ Djillali LIABES Sidi Bel Abbes, POB 89, Sidi Bel Abbes 22000, Algeria

[3] Moulay Tahar Univ Saida, Stochast Models Stat & Applicat Lab, POB 138 En Nasr Saida 20 000, Saida, Algeria

来源：

APPLICATIONS AND APPLIED MATHEMATICS-AN INTERNATIONAL JOURNAL | 2021年 / 16卷 / 01期

关键词：

Asymptotic normality; Censored data; Conditional mode; Ergodic processes functional data; Strong consistency; NONPARAMETRIC-ESTIMATION; REGRESSION ESTIMATION; QUANTILE REGRESSION; SURVIVAL FUNCTION; MODE;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this work, we investigate the asymptotic properties of a nonparametric mode of a conditional density when the real response variable is censored and the explanatory variable is valued in a semimetric space under ergodic data. First of all, we establish asymptotic properties for a conditional density estimator from which we derive an central limit theorem (CLT) of the conditional mode estimator. Simulation study is also presented to illustrate the validity and finite sample performance of the considered estimator.

引用

页码：12 / 42

页数：31

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