A recursive kernel estimate of the functional modal regression under ergodic dependence condition

In this article, we consider an alternative estimator of the conditional mode when the explanatory variable takes values in a semimetric space. This alternative estimate is based in a recursive kernel method. Under the ergodicity hypothesis, we quantify the asymptotic properties of this estimate, by...

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Bibliographic Details
Published inJournal of statistical theory and practice Vol. 10; no. 3; pp. 475 - 496
Main Authors Ardjoun, Fatima Zohra, Hennani, Larbi Ait, Laksaci, Ali
Format Journal Article
LanguageEnglish
Published Cham Taylor & Francis 02.07.2016
Springer International Publishing
Subjects
conditional distribution
conditional mode
ergodic condition
Functional data
Mathematics and Statistics
Probability Theory and Stochastic Processes
recursive estimation
Statistical Theory and Methods
Statistics
conditional distribution
62G05
conditional mode
Functional data
60G42
recursive estimation
62G20
ergodic condition
62F12
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Summary:In this article, we consider an alternative estimator of the conditional mode when the explanatory variable takes values in a semimetric space. This alternative estimate is based in a recursive kernel method. Under the ergodicity hypothesis, we quantify the asymptotic properties of this estimate, by giving the almost complete convergence rate. The asymptotic normality of this estimate is also given. Our approach is illustrated by a real data application.
ISSN:1559-8608
1559-8616
DOI:10.1080/15598608.2016.1183245