Residual empirical processes for long and short memory time series

DOI10.1214/07-AOS543zbMath1205.62128arXiv0811.0697OpenAlexW3105239596MaRDI QIDQ955149

Ngai Hang Chan, Shiqing Ling

Publication date: 18 November 2008

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

Full work available at URL: https://arxiv.org/abs/0811.0697

zbMATH Keywords

weak convergenceunit rootempirical processresidualslong-memory time series

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (10)

Correction to: Residual empirical processes for long and short memory time series ⋮ Marked empirical processes for non-stationary time series ⋮ Nonparametric conditional variance and error density estimation in regression models with dependent errors and predictors ⋮ Empirical process of residuals for regression models with long memory errors ⋮ Weak convergence of the sequential empirical processes of residuals in TAR models ⋮ Goodness-of-fit testing under long memory ⋮ On partial-sum processes of ARMAX residuals ⋮ Residual empirical processes for nearly unstable long-memory time series ⋮ Oracle-efficient estimation for functional data error distribution with simultaneous confidence band ⋮ Factor and Idiosyncratic Empirical Processes

Cites Work

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• The empirical process of some long-range dependent sequences with an application to U-statistics
• Limiting distributions of least squares estimates of unstable autoregressive processes
• Semiparametric estimation from time series with long-range dependence
• Time series regression with long-range dependence
• Asymptotic expansion of \(M\)-estimators with long-memory errors
• Limit theorems for functionals of moving averages
• Empirical processes of long-memory sequences
• Weighted empirical processes in dynamic nonlinear models.
• Limiting distributions of maximum likelihood estimators for unstable autoregressive moving-average time series with general autoregressive heteroscedastic errors
• Weak convergence of the sequential empirical processes of residuals in nonstationary autoregressive models
• On residual empirical processes of stochastic regression models with applications to time series
• On the asymptotic expansion of the empirical process of long-memory moving averages
• Weak convergence of the sequential empirical processes of residuals in ARMA models
• Log-periodogram regression of time series with long range dependence
• Gaussian semiparametric estimation of long range dependence
• Inference for unstable long-memory processes with applications to fractional unit root autoregressions
• Asymptotic distributions of the sample mean, autocovariances, and autocorrelations of long-memory time series
• Fitting an error distribution in some heteroscedastic time series models
• The Fractional Unit Root Distribution
• UNIT ROOT TESTING FOR FUNCTIONALS OF LINEAR PROCESSES
• Weak convergence to fractional brownian motion and to the rosenblatt process
• Asymptotic Distribution of Least Squares Estimators for Purely Unstable Arma (m,∞)
• ASYMPTOTICS FOR GENERAL FRACTIONALLY INTEGRATED PROCESSES WITH APPLICATIONS TO UNIT ROOT TESTS
• Testing for Parameter Constancy in Linear Regressions: An Empirical Distribution Function Approach

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