Kernel estimation for a superpopulation probability density function under informative selection

Daniel Bonnéry (), F. Jay Breidt () and François Coquet ()
Additional contact information
Daniel Bonnéry: University of Maryland
F. Jay Breidt: Colorado State University
François Coquet: Irmar and Ensai

METRON, 2017, vol. 75, issue 3, No 6, 318 pages

Abstract: Abstract Kernel density estimation of the probability density function (pdf) of a response variable is considered under informative selection from a finite population. The informative selection implies that the conditional pdf of a response, given that it was selected for observation, is not the same as the inferential target, which is the unconditional pdf of the response in the superpopulation. Instead, the pdf of the observations (sample pdf) is a weighted version of the superpopulation pdf of interest. Properties of the standard kernel density estimator are described under an asymptotic framework that covers a wide range of informative selection mechanisms. The theory allows for the possibility that the selection mechanism has a parametric structure. A variety of adjustments (parametric or nonparametric) to account for the informative selection are proposed, and investigated via simulation.

Keywords: Bochner’s lemma; Complex survey; Nadaraya-Watson estimator; Survey weighting D (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s40300-017-0127-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:metron:v:75:y:2017:i:3:d:10.1007_s40300-017-0127-x

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40300

DOI: 10.1007/s40300-017-0127-x

Access Statistics for this article

METRON is currently edited by Marco Alfo'

More articles in METRON from Springer, Sapienza Università di Roma
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().