Results 271 to 280 of about 963,951 (309)
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2003
The state space modeling tools in S+FinMetrics are based on the algorithms in SsfPack 3.0 developed by Siem Jan Koopman and described in Koopman, Shephard and Doornik (1999, 2001)1. SsfPack is a suite of C routines for carrying out computations involving the statistical analysis of univariate and multivariate models in state space form.
Eric Zivot, Jiahui Wang
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The state space modeling tools in S+FinMetrics are based on the algorithms in SsfPack 3.0 developed by Siem Jan Koopman and described in Koopman, Shephard and Doornik (1999, 2001)1. SsfPack is a suite of C routines for carrying out computations involving the statistical analysis of univariate and multivariate models in state space form.
Eric Zivot, Jiahui Wang
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2013
The nonlinear systems under consideration in this paper are described by differential equations. In the same way as for linear systems, it has system state variables, inputs and outputs. The paper provides basic definitions for state space models of nonlinear systems, and tools for preliminary analysis, including linearisation around operating points ...
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The nonlinear systems under consideration in this paper are described by differential equations. In the same way as for linear systems, it has system state variables, inputs and outputs. The paper provides basic definitions for state space models of nonlinear systems, and tools for preliminary analysis, including linearisation around operating points ...
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2021
This chapter mentions the stochastic model and defines the state-space model as a stochastic model. We also explain the features and classification of the state-space model.
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This chapter mentions the stochastic model and defines the state-space model as a stochastic model. We also explain the features and classification of the state-space model.
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1991
State space models may be regarded as generalizations of the models considered so far. They have been used extensively in system theory, the physical sciences, and engineering. The terminology is therefore largely from these fields. The general idea behind these models is that an observed (multiple) time series y 1 ,…, y T depends upon a possibly ...
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State space models may be regarded as generalizations of the models considered so far. They have been used extensively in system theory, the physical sciences, and engineering. The terminology is therefore largely from these fields. The general idea behind these models is that an observed (multiple) time series y 1 ,…, y T depends upon a possibly ...
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2017
The state space model is a very general model, mostly used to specify structural time-series models. Structural time-series models explicitly specify trends and seasonality along with other relevant influences. Under the classical Box-Jenkins time-series approach, in contrast, trends and seasonal influences are removed before estimating the core model.
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The state space model is a very general model, mostly used to specify structural time-series models. Structural time-series models explicitly specify trends and seasonality along with other relevant influences. Under the classical Box-Jenkins time-series approach, in contrast, trends and seasonal influences are removed before estimating the core model.
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2016
In this chapter, the state space model is thoroughly discussed. After defining the general state space model, the Kalman filter is derived. The square root covariance and the information filter are described. The topics of likelihood evaluation, forecasting, smoothing and covariance-based filters are discussed. Markov processes and the backwards Kalman
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In this chapter, the state space model is thoroughly discussed. After defining the general state space model, the Kalman filter is derived. The square root covariance and the information filter are described. The topics of likelihood evaluation, forecasting, smoothing and covariance-based filters are discussed. Markov processes and the backwards Kalman
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A new online modelling method for aircraft engine state space model
Chinese Journal of Aeronautics, 2020Shuwei Pang, Qiuhong Li
exaly