Goodness-of-fit test under length-biased sampling
S. M. A. Jahanshahi,
A. Habibi Rad and
V. Fakoor
Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 15, 7580-7592
Abstract:
In this article, we study a goodness-of-fit (GOF) test in the presence of length-biased sampling. For this purpose, we introduce a smoothed estimator of distribution function (d.f.) and we investigate its asymptotic behaviors, such as uniform consistency and asymptotic normality. Based on this estimator, we define a one-sample Kolmogorov type of GOF test for length-biased data. We conduct Monte Carlo simulations to evaluate the performance of the proposed test statistic and compare it with the one-sample Kolmogorov type of GOF test obtained by the non smoothed estimator of d.f.
Date: 2017
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2016.1157187 (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:15:p:7580-7592
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2016.1157187
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 ().