On Strong Consistency of Kernel Estimators Under Dependence Assumptions

J. Deddens, M. Peligrad and T. Yang
Additional contact information
J. Deddens: University of Cincinnati, Department of Mathematical Sciences
M. Peligrad: University of Cincinnati, Department of Mathematical Sciences
T. Yang: University of Cincinnati, Department of Mathematical Sciences

A chapter in Mathematical Statistics and Probability Theory, 1987, pp 33-41 from Springer

Abstract: Abstract Some considerations on the uniform consistency of the kernel estimator of a density and of a regression function are made for certain dependent samples.

Keywords: Kernel Estimator; Dependent Random Variable; Borel Measurable Function; Uniform Consistency; Bernstein Type Inequality (search for similar items in EconPapers)
Date: 1987
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-94-009-3965-3_4

Ordering information: This item can be ordered from
http://www.springer.com/9789400939653

DOI: 10.1007/978-94-009-3965-3_4

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().