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Bandwidth Selection for Recursive Kernel Density Estimators Defined by Stochastic Approximation Method
Author
Source
Journal of Probability and Statistics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-02
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
We propose an automatic selection of the bandwidth of the recursive kernel estimators of a probability density function defined by the stochastic approximation algorithm introduced by Mokkadem et al.
(2009a).
We showed that, using the selected bandwidth and the stepsize which minimize the MISE (mean integrated squared error) of the class of the recursive estimators defined in Mokkadem et al.
(2009a), the recursive estimator will be better than the nonrecursive one for small sample setting in terms of estimation error and computational costs.
We corroborated these theoretical results through simulation study.
American Psychological Association (APA)
Slaoui, Yousri. 2014. Bandwidth Selection for Recursive Kernel Density Estimators Defined by Stochastic Approximation Method. Journal of Probability and Statistics،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1042831
Modern Language Association (MLA)
Slaoui, Yousri. Bandwidth Selection for Recursive Kernel Density Estimators Defined by Stochastic Approximation Method. Journal of Probability and Statistics No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1042831
American Medical Association (AMA)
Slaoui, Yousri. Bandwidth Selection for Recursive Kernel Density Estimators Defined by Stochastic Approximation Method. Journal of Probability and Statistics. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1042831
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1042831