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Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Statistics and Probability

2020

Prairie View A&M University

Nonparametric estimation

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Nonparametric Estimation Of Trend Function For Stochastic Differential Equations Driven By A Weighted Fractional Brownian Motion, Abdelmalik Keddi, Fethi Madani, Amina A. Bouchentouf Dec 2020

Nonparametric Estimation Of Trend Function For Stochastic Differential Equations Driven By A Weighted Fractional Brownian Motion, Abdelmalik Keddi, Fethi Madani, Amina A. Bouchentouf

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we consider the problem of nonparametric estimation of trend function for stochastic differential equations driven by a weighted fractional Brownian motion (weighted-fBm). Under some general conditions, the consistent uniform, the rate of convergence as well as the asymptotic normality of our estimator are established. In addition, a numerical example is provided to illustrate the validity of the considered estimator.


Nonparametric M-Regression With Scale Parameter For Functional Dependent Data, Mebsout Mokhtaria, Attouch M. Kadi, Fetitah Omar Dec 2020

Nonparametric M-Regression With Scale Parameter For Functional Dependent Data, Mebsout Mokhtaria, Attouch M. Kadi, Fetitah Omar

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we study the equivariant nonparametric robust regression estimation relationship between a functional dependent random covariable and a scalar response. We consider a new robust regression estimator when the scale parameter is unknown. The consistency result of the proposed estimator is studied, namely the uniform almost complete convergence (with rate). Thus, suitable topological considerations are needed, implying changes in the convergence rates, which are quantified by entropy considerations. The benefits of considering robust estimators are illustrated on two real data sets where the robust fit reveals the presence of influential outliers.