On some data oriented robust estimation procedures for means

Ren-Fen Lee and Deng-Yuan Huang

Journal of Applied Statistics, 2003, vol. 30, issue 6, 625-634

Abstract: Data oriented to estimate means is very important for large data sets. Since outliers usually occur, the trimmed mean is a robust estimator of locations. After building a reasonable linear model to explain the relationship between the suitably transformed symmetric data and the approximately standardized normal statistics, we find the trimmed proportion based on the smallest variance of trimmed means. The related statistical inference is also discussed. An empirical study based on an annual survey about inbound visitors in the Taiwan area is used to achieve our goal in deciding the trimmed proportion. In this study, we propose a complete procedure to attain the goal.

Date: 2003
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/0266476032000053727 (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:japsta:v:30:y:2003:i:6:p:625-634

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20

DOI: 10.1080/0266476032000053727

Access Statistics for this article

Journal of Applied Statistics is currently edited by Robert Aykroyd

More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().