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Kernel-Type estimation of bivariate distribution for associated random variables

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Bibliographic Details
Summary:Let a stationary sequence of associated random variables with uniform distribution on [0,1] and F the distribution function of the random pair (X_1,X_{k+1}), for fixed k. We introduce a kernel estimator for F and study its asymptotic properties and moments, characterizing their convergence rates. From these we derive the optimal rate for the bandwidth, which is of order n up -1. Conditions are also given to ensure that the finite dimensional distributions are asymptotically gaussian.
Main Authors:Azevedo, Cecília Maria
Other Authors:Oliveira, Paulo
Subject:Association Convergence Kernel estimation Stationarity
Year:2000
Country:Portugal
Document type:conference paper
Access type:open access
Associated institution:Universidade do Minho
Language:English
Origin:RepositóriUM - Universidade do Minho
Description
Summary:Let a stationary sequence of associated random variables with uniform distribution on [0,1] and F the distribution function of the random pair (X_1,X_{k+1}), for fixed k. We introduce a kernel estimator for F and study its asymptotic properties and moments, characterizing their convergence rates. From these we derive the optimal rate for the bandwidth, which is of order n up -1. Conditions are also given to ensure that the finite dimensional distributions are asymptotically gaussian.