Estimation of Kramers-Moyal coefficients at low sampling rates
Data Analysis, Statistics and Probability
2011-08-25 v1
Abstract
A new optimization procedure for the estimation of Kramers-Moyal coefficients from stationary, one-dimensional, Markovian time series data is presented. The method takes advantage of a recently reported approach that allows to calculate exact finite sampling interval effects by solving the adjoint Fokker-Planck equation. Therefore it is well suited for the analysis of sparsely sampled time series. The optimization can be performed either making a parametric ansatz for drift and diffusion functions or also parameter free. We demonstrate the power of the method in several numerical examples with synthetic time series.
Keywords
Cite
@article{arxiv.1102.5264,
title = {Estimation of Kramers-Moyal coefficients at low sampling rates},
author = {Christoph Honisch and Rudolf Friedrich},
journal= {arXiv preprint arXiv:1102.5264},
year = {2011}
}
Comments
6 pages, 5 figures