scholarly journals Nonparametric estimation of the maximum of conditional hazard function under dependence conditions for functional data

2015 ◽  
Vol 10 (1) ◽  
pp. 777-794
Author(s):  
Abbes Abbes Rabhi ◽  
Yassine Hammou ◽  
Tayeb Djebbouri
Keyword(s):  
Nonparametric Estimation ◽  
Functional Data ◽  
Hazard Function ◽  
Dependence Conditions

Nonparametric estimation of the hazard function under dependence conditions

1999 ◽  
Vol 28 (10) ◽  
pp. 2294-2331 ◽  
Author(s):  
Graciela Estévez-Pérez ◽  
Alejandro Quintela-del-Río
Keyword(s):  
Nonparametric Estimation ◽  
Hazard Function ◽  
Dependence Conditions

scholarly journals Consistency rates and asymptotic normality of the high risk conditional for functional data

2015 ◽  
Vol 7 (2) ◽  
pp. 220-242
Author(s):  
Abbes Rabhi ◽  
Latifa Keddani ◽  
Yassine Hammou
Keyword(s):  
High Risk ◽  
Asymptotic Normality ◽  
Uniform Convergence ◽  
Functional Data ◽  
Hazard Function ◽  
Convergence Properties ◽  
First Derivative ◽  
Nonparametric Estimates

AbstractThe maximum of the conditional hazard function is a parameter of great importance in seismicity studies, because it constitutes the maximum risk of occurrence of an earthquake in a given interval of time. Using the kernel nonparametric estimates of the first derivative of the conditional hazard function, we establish uniform convergence properties and asymptotic normality of an estimate of the maximum in the context of independence data.

scholarly journals A Class of Local Linear Estimators with Functional Data

2019 ◽  
pp. 379-391 ◽  
Author(s):  
Sara Leulmi ◽  
Fatiha Messaci
Keyword(s):  
Nonparametric Estimation ◽  
Metric Space ◽  
Functional Data ◽  
Regression Function ◽  
Real Data ◽  
Random Variable ◽  
Data Set ◽  
Response Variable ◽  
Local Linear ◽  
Linear Estimators

We introduce a local linear nonparametric estimation for the generalized regression function of a scalar response variable given a random variable taking values in a semi metric space. We establish a rate of uniform consistency for the proposed estimators. Then, based on a real data set we illustrate the performance of a particular studied estimator with respect to other known estimators

scholarly journals Limit Law of the Local Linear Estimate of the Conditional Hazard Function for Functional Data

2020 ◽  
Author(s):  
Oussama Bouanani ◽  
Abdelhak Guendouzi ◽  
Souheyla Chemikh
Keyword(s):  
Functional Data ◽  
Hazard Function ◽  
Kernel Method ◽  
Random Variable ◽  
Nonparametric Estimator ◽  
Finite Sample ◽  
Linear Estimate ◽  
Local Linear ◽  
Local Linear Estimate ◽  
Linear Technique

In this work, we treat a prediction problem via the conditional hazard function of a scalar response variable Y given a functional random variable X by using the local linear technique. The main purpose of this paper is to investigate the asymptotic normality of the nonparametric estimator of the conditional hazard function, under some general conditions. A simulation study, conducted to assess finite sample behavior, demonstrates the superiority of our method than the standard kernel method

scholarly journals Nonparametric estimation of a convex bathtub-shaped hazard function

Bernoulli ◽  
2009 ◽  
Vol 15 (4) ◽  
pp. 1010-1035 ◽  
Author(s):  
Hanna K. Jankowski ◽  
Jon A. Wellner
Keyword(s):  
Nonparametric Estimation ◽  
Hazard Function
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