作者: J. Timmer
DOI: 10.1142/S0218127498001157
关键词: Control theory 、 Physiological tremor 、 Linear model 、 State-space representation 、 Series (mathematics) 、 Stochastic process 、 Nonlinear system 、 Noise 、 Computer science 、 Oscillation 、 Algorithm 、 Modelling and Simulation 、 Applied 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.