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Statistical estimation of a class of self-regulating processes

Abstract : Self-regulating processes are stochastic processes whose local regularity, as measured by the pointwise Hölder exponent, is a function of amplitude. They seem to provide relevant miodels for various signals arising e.g. in geophysics and biomedicine. We propose in this work an estimator of the self-regulating function (that is, the function relating amplitude and Hölder regularity) of the self-regulating midpoint displacement process introduced in [4] and study some of its properties. We prove that it is almost surely convergent and obtain a central limit theorem. Numerical simulations show that the estimator behaves well in practice.
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Contributor : Lisandro Fermin <>
Submitted on : Wednesday, August 20, 2014 - 10:27:25 AM
Last modification on : Wednesday, April 8, 2020 - 3:16:56 PM
Long-term archiving on: : Thursday, November 27, 2014 - 11:23:06 AM


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  • HAL Id : hal-00868604, version 2



Antoine Echelard, Jacques Lévy Véhel, Anne Philippe. Statistical estimation of a class of self-regulating processes. 2014. ⟨hal-00868604v2⟩



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