Identification of Persistent Cycles in Non-Gaussian Long-Memory Time Series

DOI10.1111/j.1467-9892.2008.00576.xzbMath1198.62089OpenAlexW2105568484MaRDI QIDQ3552843

Mohamed Boutahar

Publication date: 22 April 2010

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

Full work available at URL: https://doi.org/10.1111/j.1467-9892.2008.00576.x

zbMATH Keywords

Brownian motioncyclesfunctional central limit theoremslong memoryautoregressive processesleast squares estimates

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Functional limit theorems; invariance principles (60F17)

Related Items (3)

Spectral density and spectral distribution inference for long memory time series via fixed-b asymptotics ⋮ Testing for change in mean of independent multivariate observations with time varying covariance ⋮ Inducing normality from non-Gaussian long memory time series and its application to stock return data

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Noncentral limit theorems and Appell polynomials
• Zones of attraction of self-similar multiple integrals
• Limiting distributions of least squares estimates of unstable autoregressive processes
• Asymptotic normality of regression estimators with long memory errors
• Limit theorems for functionals of moving averages
• General autoregressive models with long-memory noise
• 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
• Time Series Models in Non-Normal Situations: Symmetric Innovations
• CLT and other limit theorems for functionals of Gaussian processes
• Weak convergence to fractional brownian motion and to the rosenblatt process
• Non-central limit theorems for non-linear functional of Gaussian fields
• A NOTE ON ASYMPTOTIC INFERENCE IN AUTOREGRESSIVE MODELS WITH ROOTS ON THE UNIT CIRCLE
• DISTRIBUTIONS OF LEAST SQUARES ESTIMATORS OF AUTOREGRESSIVE PARAMETERS FOR A PROCESS WITH COMPLEX ROOTS ON THE UNIT CIRCLE
• COMPLEX UNIT ROOTS AND BUSINESS CYCLES: ARE THEY REAL?
• DATA-DRIVEN NONPARAMETRIC SPECTRAL DENSITY ESTIMATORS FOR ECONOMIC TIME SERIES: A MONTE CARLO STUDY
• The Invariance Principle for Stationary Processes
• LONG MEMORY IN FINANCIAL TIME SERIES DATA WITH NON-GAUSSIAN DISTURBANCES

This page was built for publication: Identification of Persistent Cycles in Non-Gaussian Long-Memory Time Series