2016
DOI: 10.1007/s11203-016-9145-1
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Estimation of the pointwise Hölder exponent of hidden multifractional Brownian motion using wavelet coefficients

Abstract: We propose a wavelet-based approach to construct consistent estimators of the pointwise Hölder exponent of a multifractional Brownian motion, in the case where this underlying process is not directly observed. The relative merits of our estimator are discussed, and we introduce an application to the problem of estimating the functional parameter of a nonlinear model.

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Cited by 6 publications
(7 citation statements)
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References 24 publications
(48 reference statements)
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“…the observed process is of the form Φ(θ(t)X(t)), with Φ and θ being unknown C 2 -functions. In both [5] and [26], estimators of PHE with fine convergence rates are constructed and strategies for selecting input parameters are discussed.…”
Section: A General Class Of Multifractional Processesmentioning
confidence: 99%
See 4 more Smart Citations
“…the observed process is of the form Φ(θ(t)X(t)), with Φ and θ being unknown C 2 -functions. In both [5] and [26], estimators of PHE with fine convergence rates are constructed and strategies for selecting input parameters are discussed.…”
Section: A General Class Of Multifractional Processesmentioning
confidence: 99%
“…There are so far a number of estimation strategies existing in literature. We refer to [17,18,10,5,26,39] and the references therein.…”
Section: A General Class Of Multifractional Processesmentioning
confidence: 99%
See 3 more Smart Citations