On maximum likelihood estimation of the long-memory parameter in fractional Gaussian noise

DOI10.1080/00949655.2012.732076zbMath1453.62623OpenAlexW2002783463MaRDI QIDQ5219948

Wickes Robbertse, Fred Lombard

Publication date: 9 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2012.732076

zbMATH Keywords

maximum likelihood estimationlong memoryfractional Gaussian noise

Mathematics Subject Classification ID

Fractional processes, including fractional Brownian motion (60G22) Non-Markovian processes: estimation (62M09) Point estimation (62F10)

Related Items (3)

Maximum likelihood estimators from discrete data modeled by mixed fractional Brownian motion with application to the Nordic stock markets ⋮ A comparison of maximum likelihood and absolute moments for the estimation of Hurst exponents in a stationary framework ⋮ Parameter identification for the discretely observed geometric fractional Brownian motion

Uses Software

• longmemo

Cites Work

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• Efficient parameter estimation for self-similar processes
• Self-similarity in high-speed packet traffic: analysis and modeling of Ethernet traffic measurements
• Estimating the Hurst effect and its application in monitoring clinical trials
• On fast generation of fractional Gaussian noise
• Testing for long-term memory in yen/dollar exchange rate
• On the integral of the squared periodogram
• Fractional Brownian motion and clinical trials

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