Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/11474
Title: Bivariante distribution function estimation for associated variables
Authors: Azevedo, Cecília 
Oliveira, Paulo Eduardo 
Issue Date: 2000
Publisher: Centro de Matemática da Universidade de Coimbra
Citation: Pré-Publicações DMUC. 00-16 (2000)
Abstract: The estimation of distribution functions of pairs of associated variables is addressed based on a kernel estimator. This problem is motivated by the need to approximate covariance functions appearing as the limiting covariances of the empirical process sequence. Results characterizing the asymptotics and convergence rates of the estimator are obtained. From these we derive the optimal bandwidth convergence rate, which is of order n-1 . Finally, we give conditions for the asymptotic normality of the finite dimensional distributions, characterizing their limit covariance matrix. Besides some usual conditions on the kernel function, the conditions typically impose a convenient decrease rate on the covariances Cov(X1 , X n ).
URI: http://hdl.handle.net/10316/11474
Rights: openAccess
Appears in Collections:FCTUC Matemática - Artigos em Revistas Nacionais

Files in This Item:
File Description SizeFormat 
Bivariante distribution function estimation for associated variables.pdf232.02 kBAdobe PDFView/Open
Show full item record

Page view(s)

195
checked on Jul 16, 2019

Download(s)

11
checked on Jul 16, 2019

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.