Single Functional Index Model under Responses MAR and Dependent Observations

2020 ◽  
pp. 161-168
Author(s):  
Nengxiang Ling ◽  
Lilei Cheng ◽  
Philippe Vieu
Keyword(s):  
Functional Index ◽  
Index Model ◽  
Dependent Observations

scholarly journals Strong uniform consistency rates of conditional quantile estimation in the single functional index model under random censorship

2018 ◽  
Vol 6 (1) ◽  
pp. 197-227 ◽  
Author(s):  
Nadia Kadiri ◽  
Abbes Rabhi ◽  
Amina Angelika Bouchentouf
Keyword(s):  
Cumulative Distribution Function ◽  
Complete Convergence ◽  
Asymptotic Properties ◽  
Cumulative Distribution ◽  
Index Structure ◽  
Functional Index ◽  
Conditional Quantile ◽  
Index Model ◽  
Strong Uniform Consistency ◽  
Mixing Sequence

AbstractThe main objective of this paper is to non-parametrically estimate the quantiles of a conditional distribution in the censorship model when the sample is considered as an -mixing sequence. First of all, a kernel type estimator for the conditional cumulative distribution function (cond-cdf) is introduced. Afterwards, we estimate the quantiles by inverting this estimated cond-cdf and state the asymptotic properties when the observations are linked with a single-index structure. The pointwise almost complete convergence and the uniform almost complete convergence (with rate) of the kernel estimate of this model are established. This approach can be applied in time series analysis.

Cross-validated estimations in the single-functional index model

Statistics ◽  
2008 ◽  
Vol 42 (6) ◽  
pp. 475-494 ◽  
Author(s):  
Ahmed Ait-Saïdi ◽  
Frédéric Ferraty ◽  
Rabah Kassa ◽  
Philippe Vieu
Keyword(s):  
Functional Index ◽  
Index Model

scholarly journals CLT for single functional index quantile regression under dependence structure

2021 ◽  
Vol 13 (1) ◽  
pp. 45-77
Author(s):  
Nadia Kadiri ◽  
Abbes Rabhi ◽  
Salah Khardani ◽  
Fatima Akkal
Keyword(s):  
Asymptotic Properties ◽  
Likelihood Method ◽  
Dependence Structure ◽  
Finite Sample ◽  
Functional Index ◽  
Conditional Quantile ◽  
Index Model ◽  
Conditional Quantile Estimator ◽  
Pseudo Maximum Likelihood ◽  
Random Responses

Abstract In this paper, we investigate the asymptotic properties of a nonparametric conditional quantile estimation in the single functional index model for dependent functional data and censored at random responses are observed. First of all, we establish asymptotic properties for a conditional distribution estimator from which we derive an central limit theorem (CLT) of the conditional quantile estimator. Simulation study is also presented to illustrate the validity and finite sample performance of the considered estimator. Finally, the estimation of the functional index via the pseudo-maximum likelihood method is discussed, but not tackled.

A partitioned Single Functional Index Model

2014 ◽  
Vol 30 (3) ◽  
pp. 673-692 ◽  
Author(s):  
Aldo Goia ◽  
Philippe Vieu
Keyword(s):  
Functional Index ◽  
Index Model

scholarly journals A note on the conditional density estimate in the single functional index model

2011 ◽  
Vol 81 (1) ◽  
pp. 45-53 ◽  
Author(s):  
Said Attaoui ◽  
Ali Laksaci ◽  
Elias Ould Said
Keyword(s):  
Density Estimate ◽  
Conditional Density ◽  
Functional Index ◽  
Index Model
Sign in / Sign up

Export Citation Format

Share Document