Nonparametric local linear estimation of the relative error regression function for censorship model

04/06/2020
by   Feriel Bouhadjera, et al.
0

In this paper, we built a new nonparametric regression estimator with the local linear method by using the mean squared relative error as a loss function when the data are subject to random right censoring. We establish the uniform almost sure consistency with rate over a compact set of the proposed estimator. Some simulations are given to show the asymptotic behavior of the estimate in different cases.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/28/2019

Nonparametric relative error estimation of the regression function for censored data

Let (T_i)_i be a sequence of independent identically distributed (i.i.d...
research
04/06/2020

Strong consistency of the nonparametric local linear regression estimation under censorship model

We introduce and study a local linear nonparametric regression estimator...
research
10/04/2019

On the strong uniform consistency for relative error of the regression function estimator for censoring times series model

Consider a random vector (X, T), where X is d-dimensional and T is one-d...
research
10/03/2018

Estimating the error distribution function in nonparametric regression

We construct an efficient estimator for the error distribution function ...
research
06/27/2022

Benign overfitting and adaptive nonparametric regression

In the nonparametric regression setting, we construct an estimator which...
research
11/22/2021

Nonparametric estimator of the tail dependence coefficient: balancing bias and variance

A theoretical expression is derived for the mean squared error of a nonp...
research
07/27/2023

One-step nonparametric instrumental regression using smoothing splines

We extend nonparametric regression smoothing splines to a context where ...

Please sign up or login with your details

Forgot password? Click here to reset