Modeling Noisy Time Series: Physiological Tremor

作者: J. Timmer

DOI: 10.1142/S0218127498001157

关键词: Control theoryPhysiological tremorLinear modelState-space representationSeries (mathematics)Stochastic processNonlinear systemNoiseComputer scienceOscillationAlgorithmModelling and SimulationApplied mathematics

摘要: Empirical time series often contain observational noise. We investigate the effect of this noise on the estimated parameters of models fitted to the data. For data of physiological tremor, i.e. a small amplitude oscillation of the outstretched hand of healthy subjects, we compare the results for a linear model that explicitly includes additional observational noise to one that ignores this noise. We discuss problems and possible solutions for nonlinear deterministic as well as nonlinear stochastic processes. Especially we discuss the state space model applicable for modeling noisy stochastic systems and Bock's algorithm capable for modeling noisy deterministic systems.

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