Comparison of difference based variance estimators for partially linear models

Guoyi Zhang and Yan Lu

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 23, 8454-8466

Abstract: In this research, we evaluated two difference based variance estimators: one by Gasser, Sroka, and Jennen-Steinmetz, and another by Hall, Kay, and Titterington for use in partially linear models. Under various settings, we compared power of tests for heteroskedasticity, and other finite population properties of the estimators using simulation studies. We also proved that under regularity conditions, the estimator from Hall, Kay, and Titterington provides larger power of the tests for heteroskedasticity. A real example is given to illustrate the usage of the estimators.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2022.2064498 (text/html)
Access to full text is restricted to subscribers.

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:taf:lstaxx:v:52:y:2023:i:23:p:8454-8466

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2022.2064498

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().