Computer-intensive rate estimation, diverging statistics and scanning

DOI10.1214/009053607000000064zbMath1209.62050arXiv0710.5004OpenAlexW3099831077MaRDI QIDQ2456022

Dimitris N. Politis, Tucker S. McElroy

Publication date: 17 October 2007

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0710.5004

zbMATH Keywords

convergence ratelong memorysubsamplingheavy tail index

Mathematics Subject Classification ID

Related Items (11)

Fixed-smoothing asymptotics in the generalized empirical likelihood estimation framework ⋮ Subsampling inference for the mean of heavy-tailed long-memory time series ⋮ Online Covariance Matrix Estimation in Stochastic Gradient Descent ⋮ Tail index estimation in the presence of long-memory dynamics ⋮ Detection of long range dependence in the time domain for (in)finite-variance time series ⋮ A nonstandard empirical likelihood for time series ⋮ Distribution theory for the Studentized mean for long, short, and negative memory time series ⋮ Spectral density and spectral distribution inference for long memory time series via fixed-b asymptotics ⋮ FIXED-B ASYMPTOTICS FOR THE STUDENTIZED MEAN FROM TIME SERIES WITH SHORT, LONG, OR NEGATIVE MEMORY ⋮ On the measurement and treatment of extremes in time series ⋮ Summability of stochastic processes -- a generalization of integration for non-linear processes

Uses Software

• longmemo

Cites Work

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• THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS
• Weak convergence to fractional brownian motion and to the rosenblatt process
• Convergence of integrated processes of arbitrary Hermite rank
• On Subsampling Estimators with Unknown Rate of Convergence
• Joint exceedances of the ARCH process
• ROBUST INFERENCE FOR THE MEAN IN THE PRESENCE OF SERIAL CORRELATION AND HEAVY-TAILED DISTRIBUTIONS
• Using a bootstrap method to choose the sample fraction in tail index estimation

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