Saddlepoint approximation for the kernel density estimator

Cyrille Joutard

Statistics & Probability Letters, 2025, vol. 226, issue C

Abstract: Assuming real and independent and identically distributed observations, we obtain a classical pointwise saddlepoint approximation for the tail probability of the Parzen–Rosenblatt density estimator. This saddlepoint approximation is similar to the one which was first obtained by Daniels (1987) for the sample mean via the method of indirect Edgeworth expansion.

Keywords: Nonparametric estimation; Kernel density estimator; Saddlepoint approximation; Indirect Edgeworth expansion (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715225001671
Full text for ScienceDirect subscribers only

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:eee:stapro:v:226:y:2025:i:c:s0167715225001671

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.spl.2025.110522

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().