Parametric estimation for cusp-type signal driven by fractional Brownian motion

DOI10.1080/07362994.2019.1646140zbMath1436.62408OpenAlexW2964505539WikidataQ127398532 ScholiaQ127398532MaRDI QIDQ5206079

B. L. S. Prakasa Rao, Mahendra Nath Mishra

Publication date: 18 December 2019

Published in: Stochastic Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07362994.2019.1646140

zbMATH Keywords

stochastic differential equationfractional Brownian motionstochastic processestimation of parametersmaximum likelihood methoddrift parameter

Mathematics Subject Classification ID

Fractional processes, including fractional Brownian motion (60G22) Non-Markovian processes: estimation (62M09) Point estimation (62F10) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10)

Related Items (2)

Estimation for misspecification when theoretical model for signal is smooth but real signal is of cusp-type and driven by a fractional Brownian motion ⋮ Fractional processes and their statistical inference: an overview

Cites Work

• Asymptotic theory of least squares estimator in a nonregular nonlinear regression model
• An elementary approach to a Girsanov formula and other analytical results on fractional Brownian motions
• Estimation of cusp in nonregular nonlinear regression models.
• On parameter estimation for cusp-type signals
• Stochastic calculus for fractional Brownian motion and related processes.
• Estimation of change point for switching fractional diffusion processes
• Statistical Inference for Fractional Diffusion Processes
• Estimation of the Location of the Cusp of a Continuous Density
• Parameter estimation and optimal filtering for fractional type stochastic systems
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