Estimators of contingent probabilities and means with actuarial applications

Liang Hong

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 2, 927-941

Abstract: Contingent probabilities and means are ubiquitous in actuarial science. The correct interpretation of contingent probabilities and means as well as the probability theory behind them have been addressed by researchers. In this article, we explore their statistical aspect. We give non-parametric estimators of contingent probabilities and means. Then, we show that our estimators are strongly consistent. Moreover, we give the asymptotic distributions of our estimators. Finally, we provide several examples to demonstrate the applications of these estimators in actuarial science.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2015.1010003 (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:46:y:2017:i:2:p:927-941

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

DOI: 10.1080/03610926.2015.1010003

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 ().