Non‐parametric Regression with Dependent Censored Data

Anouar El Ghouch and Ingrid Van Keilegom ()

Scandinavian Journal of Statistics, 2008, vol. 35, issue 2, 228-247

Abstract: Abstract. Let (Xi,Yi) (i=1,…,n) be n replications of a random vector (X,Y ), where Y is supposed to be subject to random right censoring. The data (Xi,Yi) are assumed to come from a stationary α‐mixing process. We consider the problem of estimating the function m(x) =ℰ(φ(Y) | X=x), for some known transformation φ. This problem is approached in the following way: first, we introduce a transformed variable , that is not subject to censoring and satisfies the relation , and then we estimate m(x) by applying local linear regression techniques. As a by‐product, we obtain a general result on the uniform rate of convergence of kernel type estimators of functionals of an unknown distribution function, under strong mixing assumptions.

Date: 2008
References: View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9469.2007.00586.x

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:bla:scjsta:v:35:y:2008:i:2:p:228-247

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0303-6898

Access Statistics for this article

Scandinavian Journal of Statistics is currently edited by ÿrnulf Borgan and Bo Lindqvist

More articles in Scandinavian Journal of Statistics from Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association, Swedish Statistical Association
Bibliographic data for series maintained by Wiley Content Delivery ().