Finite sampling interval effects in Kramers-Moyal analysis

Steven J. Lade*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    37 Citations (Scopus)

    Abstract

    Large sampling intervals can affect reconstruction of Kramers-Moyal coefficients from data. A new method, which is direct, non-stochastic and exact up to numerical accuracy, is developed to estimate these finite time effects. The method is applied numerically to biologically inspired examples. Exact finite time effects are also described analytically for two special cases. The approach developed will permit better evaluation of Langevin or Fokker-Planck based models from data with large sampling intervals. It can also be used to predict the sampling intervals for which finite time effects become significant.

    Original languageEnglish
    Pages (from-to)3705-3709
    Number of pages5
    JournalPhysics Letters, Section A: General, Atomic and Solid State Physics
    Volume373
    Issue number41
    DOIs
    Publication statusPublished - 5 Oct 2009

    Fingerprint

    Dive into the research topics of 'Finite sampling interval effects in Kramers-Moyal analysis'. Together they form a unique fingerprint.

    Cite this