Journal
PHYSICAL REVIEW E
Volume 65, Issue 5, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.65.056201
Keywords
-
Categories
Ask authors/readers for more resources
We analyze prediction schemes for stochastic time series data. We propose that under certain conditions, a scalar time series, obtained from a vector-valued Markov process can be modeled as a finite memory Markov process in the observable. The transition rules of the process are easily computed using simple nonlinear time series predictors originally Proposed for deterministic chaotic signals. The optimal time lag entering the embedding procedure is shown to be significantly smaller than the deterministic cas e. The concept is illustrated for simulated data and for surface wind velocity data, for which the deterministic part of the dynamics is shown to be nonlinear.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available