Estimating Kramers-Moyal coefficients in short and non-stationary data sets

A.M. van Mourik; A. Daffertshofer; P.J. Beek

doi:10.1016/j.physleta.2005.10.066

Estimating Kramers-Moyal coefficients in short and non-stationary data sets

A.M. van Mourik
, A. Daffertshofer
, P.J. Beek

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

To reliably estimate the dynamics of diffusive Markov processes, we combine statistically independent empirical data. Since commutative statistics do not affect fundamental Markov properties, they provide robust estimators for Kramers-Moyal coefficients even when registration time and sampling frequency of individual recordings are rather limited. We also show how the results of the method can be further improved and extended in order to apply it in the non-stationary regime. © 2005 Elsevier B.V. All rights reserved.

Original language	English
Pages (from-to)	13-7
Journal	Physics Letters A
Volume	351
DOIs	https://doi.org/10.1016/j.physleta.2005.10.066
Publication status	Published - 2006

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10.1016/j.physleta.2005.10.066

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abstract = "To reliably estimate the dynamics of diffusive Markov processes, we combine statistically independent empirical data. Since commutative statistics do not affect fundamental Markov properties, they provide robust estimators for Kramers-Moyal coefficients even when registration time and sampling frequency of individual recordings are rather limited. We also show how the results of the method can be further improved and extended in order to apply it in the non-stationary regime. {\textcopyright} 2005 Elsevier B.V. All rights reserved.",

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AB - To reliably estimate the dynamics of diffusive Markov processes, we combine statistically independent empirical data. Since commutative statistics do not affect fundamental Markov properties, they provide robust estimators for Kramers-Moyal coefficients even when registration time and sampling frequency of individual recordings are rather limited. We also show how the results of the method can be further improved and extended in order to apply it in the non-stationary regime. © 2005 Elsevier B.V. All rights reserved.

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JF - Physics Letters A

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Estimating Kramers-Moyal coefficients in short and non-stationary data sets

Abstract

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