A Note on Bias of Closed-Form Estimators for the Gamma Distribution Derived From Likelihood Equations

Francisco Louzada, Pedro L. Ramos and Eduardo Ramos

The American Statistician, 2019, vol. 73, issue 2, 195-199

Abstract: We discuss here an alternative approach for decreasing the bias of the closed-form estimators for the gamma distribution recently proposed by Ye and Chen in 2017. We show that, the new estimator has also closed-form expression, is positive, and can be computed for n > 2. Moreover, the corrective approach returns better estimates when compared with the former ones.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/00031305.2018.1513376 (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:amstat:v:73:y:2019:i:2:p:195-199

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UTAS20

DOI: 10.1080/00031305.2018.1513376

Access Statistics for this article

The American Statistician is currently edited by Eric Sampson

More articles in The American Statistician from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().