VALIDITY OF THE SAMPLING WINDOW METHOD FOR LONG-RANGE DEPENDENT LINEAR PROCESSES

DOI10.1017/S0266466605050541zbMath1083.62094MaRDI QIDQ3377444

Daniel J. Nordman, Soumendra Nath Lahiri

Publication date: 22 March 2006

Published in: Econometric Theory (Search for Journal in Brave)

zbMATH Keywords

tables

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Non-Markovian processes: estimation (62M09) Nonparametric tolerance and confidence regions (62G15)

Related Items (12)

A unified approach to self-normalized block sampling ⋮ Properties of a block bootstrap under long-range dependence ⋮ Subsampling inference for the mean of heavy-tailed long-memory time series ⋮ On robust tail index estimation for linear long-memory processes ⋮ Confidence regions for entries of a large precision matrix ⋮ Rank-based change-point analysis for long-range dependent time series ⋮ Block Bootstrap for the Empirical Process of Long‐Range Dependent Data ⋮ Block sampling under strong dependence ⋮ Convolved subsampling estimation with applications to block bootstrap ⋮ How the instability of ranks under long memory affects large-sample inference ⋮ Empirical likelihood confidence intervals for the mean of a long‐range dependent process ⋮ On optimal block resampling for Gaussian-subordinated long-range dependent processes

Cites Work

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• Weak convergence to fractional brownian motion and to the rosenblatt process
• Law of the iterated logarithm for sums of non-linear functions of Gaussian variables that exhibit a long range dependence
• Convergence of integrated processes of arbitrary Hermite rank
• Non-central limit theorems for non-linear functional of Gaussian fields
• Fractional Brownian Motions, Fractional Noises and Applications
• The Invariance Principle for Stationary Processes

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