Asymptotic properties of conditional quantile estimator for censored dependent observations

Content Provider	Semantic Scholar
Author	Liang, Han-Ying Uña-Álvarez, Jacobo De
Copyright Year	2011
Abstract	In this paper, we establish strong uniform convergence and asymptotic normality of the conditional quantile estimator for the censorship model when the data exhibit some kind of dependence. It is assumed that the observations form a stationary α-mixing sequence. The strong uniform convergence in iid framework has recently been discussed by Ould-Saïd (Stat Probab Lett 76:579–586, 2006). As a by-product, we also obtain a uniform weak convergence rate for the product-limit estimator of the lifetime and censoring distributions under dependence, which is interesting independently.
Starting Page	267
Ending Page	289
Page Count	23
File Format	PDF HTM / HTML
DOI	10.1007/s10463-009-0230-8
Alternate Webpage(s)	https://www.ism.ac.jp/editsec/aism/63/0267.pdf
Alternate Webpage(s)	https://www.ism.ac.jp/editsec/aism/pdf/10463_2009_Article_230.pdf
Alternate Webpage(s)	https://doi.org/10.1007/s10463-009-0230-8
Volume Number	63
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article