Quasi‐Maximum Likelihood Estimation for a Class of Continuous‐time Long‐memory Processes

DOI10.1111/j.1467-9892.2005.00422.xzbMath1091.62090OpenAlexW3125181064MaRDI QIDQ5467623

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Publication date: 24 May 2006

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

Full work available at URL: https://doi.org/10.1111/j.1467-9892.2005.00422.x

zbMATH Keywords

asymptotic normalityWhittle likelihoodcontinuous time autoregressive fractionally integrated moving-average process

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and spectral analysis (62M15) Large deviations (60F10)

Related Items (21)

Whittle estimation for continuous-time stationary state space models with finite second moments ⋮ Statistical inference for stationary linear models with tapered data ⋮ Frequency-domain identification of continuous-time ARMA models from sampled data ⋮ Moment method estimation of first-order continuous-time bilinear processes ⋮ Explicit analytical solutions for ARL of CUSUM chart for a long-memory SARFIMA model ⋮ On continuous-time autoregressive fractionally integrated moving average processes ⋮ Multivariate supOU processes ⋮ Robust estimation for continuous-time linear models with memory ⋮ Maximum likelihood estimators of a long-memory process from discrete observations ⋮ Bayesian inference of the fractional Ornstein-Uhlenbeck process under a flow sampling scheme ⋮ The exact discrete model of a system of linear stochastic differential equations driven by fractional noise ⋮ On the robustness to small trends of parameter estimation for continuous-time stationary models with memory ⋮ EM-based identification of continuous-time ARMA models from irregularly sampled data ⋮ A new simple test against spurious long memory using temporal aggregation ⋮ Parameter estimation for Lévy-driven continuous-time linear models with tapered data ⋮ Random discretization of stationary continuous time processes ⋮ Temporal Aggregation of Stationary and Non‐stationary Continuous‐Time Processes ⋮ Two-step wavelet-based estimation for Gaussian mixed fractional processes ⋮ Limit theorems for Toeplitz-type quadratic functionals of stationary processes and applications ⋮ On the asymptotic properties of a feasible estimator of the continuous time long memory parameter ⋮ Statistical estimation for stationary models with tapered data

Uses Software

• longmemo

Cites Work

• Continuous-time fractional ARMA processes
• State space modeling of long-memory processes
• The problem of identification in finite parameter continuous time models
• Long memory processes and fractional integration in econometrics
• Long memory continuous time models
• A central limit theorem for quadratic forms in strongly dependent linear variables and its application to asymptotical normality of Whittle's estimate
• Bandwidth selection for kernel regression with long-range dependent errors
• Stochastic Calculus for Fractional Brownian Motion I. Theory
• Fractional Brownian Motions, Fractional Noises and Applications
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