Nonparametric density estimation for a long-range dependent linear process

DOI10.1023/A:1017504723799zbMath0978.62029MaRDI QIDQ5936202

Toshio Honda

Publication date: 4 February 2002

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

zbMATH Keywords

asymptotic normalitybandwidthlinear processkernel density estimatorlong-range dependence

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20)

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Estimating invariant laws of linear processes by \(U\)-statistics. ⋮ On nonparametric density estimation for multivariate linear long-memory processes ⋮ Root-\(n\) consistency in weighted \(L _{1}\)-spaces for density estimators of invertible linear processes ⋮ Efficient density estimation in an AR(1) model ⋮ Memory properties of transformations of linear processes ⋮ Functional convergence and optimality of plug-in estimators for stationary densities of moving average processes ⋮ Kernel density estimation for linear processes ⋮ On estimating the cumulant generating function of linear processes ⋮ Uniformly root-\(n\) consistent density estimators for weakly dependent invertible linear proc\-esses ⋮ Nonparametric density estimation for linear processes with infinite variance ⋮ Testing for the expected number of exceedances in strongly dependent seasonal time series

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