Nonparametric relative recursive regression

Autor:	Slaoui Yousri, Khardani Salah
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	nonparametric regression stochastic approximation algorithm smoothing curve fitting relative regression 62g08 62l20 65d10 Science (General) Q1-390 Mathematics QA1-939
Zdroj:	Dependence Modeling, Vol 8, Iss 1, Pp 221-238 (2020)
Druh dokumentu:	article
ISSN:	2300-2298 2020-0013
DOI:	10.1515/demo-2020-0013
Popis:	In this paper, we propose the problem of estimating a regression function recursively based on the minimization of the Mean Squared Relative Error (MSRE), where outlier data are present and the response variable of the model is positive. We construct an alternative estimation of the regression function using a stochastic approximation method. The Bias, variance, and Mean Integrated Squared Error (MISE) are computed explicitly. The asymptotic normality of the proposed estimator is also proved. Moreover, we conduct a simulation to compare the performance of our proposed estimators with that of the two classical kernel regression estimators and then through a real Malaria dataset.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/6d13e30a4c714d3fa5dfd47c137bd85a Zobrazit plný text záznamu View record in DOAJ