Estimation of the memory parameter by fitting fractionally differenced autoregressive models

DOI10.1016/j.jmva.2006.01.003zbMath1101.62073OpenAlexW2142728798MaRDI QIDQ853943

R. J. Bhansali, Liudas Giraitis, Piotr S. Kokoszka

Publication date: 7 December 2006

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2006.01.003

zbMATH Keywords

central limit theoremlong memoryautoregressive estimationspectral norm bounds

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20)

Related Items (8)

Approximations and limit theory for quadratic forms of linear processes ⋮ Frequency domain bootstrap for ratio statistics under long-range dependence ⋮ Adaptive semiparametric wavelet estimator and goodness-of-fit test for long-memory linear processes ⋮ Maximum likelihood estimators of a long-memory process from discrete observations ⋮ A GENERALIZED PORTMANTEAU TEST FOR INDEPENDENCE BETWEEN TWO STATIONARY TIME SERIES ⋮ The FEXP estimator for potentially non-stationary linear time series. ⋮ Adaptive wavelet-based estimator of the memory parameter for stationary Gaussian processes ⋮ Broadband semi-parametric estimation of long-memory time series by fractional exponential models

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