Please use this identifier to cite or link to this item:
http://doi.org/10.25358/openscience-5803
Authors: | Höpfner, Reinhard |
Title: | Polynomials under Ornstein–Uhlenbeck noise and an application to inference in stochastic Hodgkin–Huxley systems |
Online publication date: | 11-May-2021 |
Year of first publication: | 2021 |
Language: | english |
Abstract: | We discuss estimation problems where a polynomial s→∑ℓi=0ϑisi with strictly positive leading coefficient is observed under Ornstein–Uhlenbeck noise over a long time interval. We prove local asymptotic normality (LAN) and specify asymptotically efficient estimators. We apply this to the following problem: feeding noise dYt into the classical (deterministic) Hodgkin–Huxley model in neuroscience, with Yt=ϑt+Xt and X some Ornstein–Uhlenbeck process with backdriving force τ, we have asymptotically efficient estimators for the pair (ϑ,τ); based on observation of the membrane potential up to time n, the estimate for ϑ converges at rate n3−−−√. |
DDC: | 510 Mathematik 510 Mathematics |
Institution: | Johannes Gutenberg-Universität Mainz |
Department: | FB 08 Physik, Mathematik u. Informatik |
Place: | Mainz |
ROR: | https://ror.org/023b0x485 |
DOI: | http://doi.org/10.25358/openscience-5803 |
Version: | Published version |
Publication type: | Zeitschriftenaufsatz |
License: | CC BY |
Information on rights of use: | https://creativecommons.org/licenses/by/4.0/ |
Journal: | Statistical inference for stochastic processes 24 |
Pages or article number: | 35 59 |
Publisher: | Springer Science + Business Media B.V. |
Publisher place: | Dordrecht |
Issue date: | 2021 |
ISSN: | 1572-9311 |
Publisher URL: | https://doi.org/10.1007/s11203-020-09226-0 |
Publisher DOI: | 10.1007/s11203-020-09226-0 |
Appears in collections: | JGU-Publikationen |
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höpfner_reinhard-polynomials_un-20210421200155509.pdf | 525.45 kB | Adobe PDF | View/Open |