Strong Gaussian approximations of product-limit and quantile processes for truncated data under strong mixing

M. Bolbolian Ghalibaf, V. Fakoor and H.A. Azarnoosh

Statistics & Probability Letters, 2010, vol. 80, issue 7-8, 581-586

Abstract: In this paper, we consider the product-limit quantile estimator of an unknown quantile function under a truncated dependent model. This is a parallel problem to the estimation of the unknown distribution function by the product-limit estimator under the same model. Simultaneous strong Gaussian approximations of the product-limit process and normed product-limit quantile process are constructed with rate O((logn)-[lambda]) for some [lambda]>0. The strong Gaussian approximation of the product-limit process is then applied to derive the law of the iterated logarithm for the product-limit process.

Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(09)00471-4
Full text for ScienceDirect subscribers only

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:eee:stapro:v:80:y:2010:i:7-8:p:581-586

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().