Asymptotically efficient estimators for self-similar stationary Gaussian noises under high frequency observations

DOI10.3150/18-BEJ1039zbMath1466.62382arXiv1611.07276OpenAlexW2963500117WikidataQ127708273 ScholiaQ127708273MaRDI QIDQ2419663

Tetsuya Takabatake, Masaaki Fukasawa

Publication date: 14 June 2019

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1611.07276

zbMATH Keywords

asymptotic efficiencylocal asymptotic normalityhigh frequency observationsWhittle estimationfractional Gaussian noises

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Fractional processes, including fractional Brownian motion (60G22) Non-Markovian processes: estimation (62M09) Inference from stochastic processes and spectral analysis (62M15) Self-similar stochastic processes (60G18)

Related Items (7)

Consistent estimation for fractional stochastic volatility model under high‐frequency asymptotics ⋮ Asymptotically efficient estimators for self-similar stationary Gaussian noises under high frequency observations ⋮ Optimal estimation of the rough Hurst parameter in additive noise ⋮ High-frequency analysis of parabolic stochastic PDEs ⋮ Asymptotically efficient estimation of ergodic rough fractional Ornstein-Uhlenbeck process under continuous observations ⋮ Unnamed Item ⋮ One-step estimation for the fractional Gaussian noise at high-frequency

Uses Software

• YUIMA

Cites Work

• Unnamed Item
• Efficient parameter estimation for self-similar processes
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• Parameter estimation for the discretely observed fractional Ornstein-Uhlenbeck process and the Yuima R package
• Asymptotically efficient estimators for self-similar stationary Gaussian noises under high frequency observations
• LAN property for some fractional type Brownian motion
• Self-Similar Probability Distributions
• Fisher Information for Fractional Brownian Motion Under High-Frequency Discrete Sampling
• ASYMPTOTIC THEORY FOR MAXIMUM LIKELIHOOD ESTIMATION OF THE MEMORY PARAMETER IN STATIONARY GAUSSIAN PROCESSES
• Fractional Brownian Motions, Fractional Noises and Applications
• Estimating the parameters of a fractional Brownian motion by discrete variations of its sample paths

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