Corrigendum to ‘Subsampling Inference for the Mean of Heavy‐Tailed Long‐Memory Time Series’ by A. Jach, T. S. McElroy and D. N. Politis

DOI10.1111/jtsa.12191zbMath1416.62499OpenAlexW2305251066MaRDI QIDQ2817318

Agnieszka Jach, Dimitris N. Politis, Tucker S. McElroy

Publication date: 30 August 2016

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/jtsa.12191

zbMATH Keywords

heavy tailsweak dependencesubsampling

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: estimation (62M09) Applications of statistics in engineering and industry; control charts (62P30) Statistics of extreme values; tail inference (62G32)

Related Items (3)

Rank-based change-point analysis for long-range dependent time series ⋮ The Slow Convergence of Ordinary Least Squares Estimators of α, β and Portfolio Weights under Long‐Memory Stochastic Volatility ⋮ On optimal block resampling for Gaussian-subordinated long-range dependent processes

Cites Work

• A unified approach to self-normalized block sampling
• A new weak dependence condition and applications to moment inequalities
• Subsampling weakly dependent time series and application to extremes
• Subsampling inference for the mean of heavy-tailed long-memory time series
• On Joint Fourier–Laplace Transforms

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