Boundary Bias Correction Using Weighting Method in Presence of Nonresponse in Two-Stage Cluster Sampling

Nelson Kiprono Bii, Christopher Ouma Onyango and John Odhiambo

Journal of Probability and Statistics, 2019, vol. 2019, 1-8

Abstract:

Kernel density estimators due to boundary effects are often not consistent when estimating a density near a finite endpoint of the support of the density to be estimated. To address this, researchers have proposed the application of an optimal bandwidth to balance the bias-variance trade-off in estimation of a finite population mean. This, however, does not eliminate the boundary bias. In this paper weighting method of compensating for nonresponse is proposed. Asymptotic properties of the proposed estimator of the population mean are derived. Under mild assumptions, the estimator is shown to be asymptotically consistent.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/JPS/2019/6812795.pdf (application/pdf)
http://downloads.hindawi.com/journals/JPS/2019/6812795.xml (text/xml)

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:hin:jnljps:6812795

DOI: 10.1155/2019/6812795

Access Statistics for this article

More articles in Journal of Probability and Statistics from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().