Estimating the Hurst effect and its application in monitoring clinical trials

DOI10.1016/S0167-9473(03)00085-9zbMath1429.62559MaRDI QIDQ956853

Dejian Lai

Publication date: 26 November 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

zbMATH Keywords

fractional Brownian motionclinical trialsmaximum likelihood methodHurst coefficientsimulation studiessymptotic normality

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Fractional processes, including fractional Brownian motion (60G22) Non-Markovian processes: estimation (62M09)

Related Items (14)

Sample size determination for group sequential test under fractional Brownian motion ⋮ Experimental study of the influence of an irregular sample on the estimation of the Hurst parameter ⋮ Fractional Brownian motion and long term clinical trial recruitment ⋮ Asymptotic normality of the estimators for fractional Brownian motions with discrete data ⋮ Sample Size Re-Estimation Based on Two-Stage Analysis of Variance: Interim Analysis of Clinical Trials ⋮ Operating Characteristics for Group Sequential Trials Monitored Under Fractional Brownian Motion ⋮ Repeated confidence intervals and prediction intervals using stochastic curtailment under fractional Brownian motion ⋮ On maximum likelihood estimation of the long-memory parameter in fractional Gaussian noise ⋮ Estimation of Hurst exponent revisited ⋮ Repeated Confidence Intervals Under Fractional Brownian Motion in Long-Term Clinical Trials ⋮ Asymmetric Group Sequential Designs under Fractional Brownian Motion ⋮ Stochastically Curtailed Tests Under Fractional Brownian Motion ⋮ Parameter Identification for Drift Fractional Brownian Motions with Application to the Chinese Stock Markets ⋮ Group sequential tests under fractional Brownian motion in monitoring clinical trials

Uses Software

• IMSL Numerical Libraries
• longmemo

Cites Work

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• A DYNAMICAL APPROACH TO FRACTIONAL BROWNIAN MOTION

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