Subdue
发表于 2025-3-25 07:18:04
https://doi.org/10.1007/978-3-030-20790-8Linear time series; MATLAB; State space models; Kalman filter; Univariate time series; Multivariate time
overrule
发表于 2025-3-25 10:25:19
Quick Introduction to SSMMATLAB,In this chapter, we will present some examples on how SSMMATLAB can easily handle some of the more popular univariate and multivariate time series models. In this way, the user can quickly familiarize himself/herself with this software tool.
BLOT
发表于 2025-3-25 13:14:04
Stationarity, VARMA, and ARIMA Models,Statistically speaking, a . is a finite set of values {..…, ..} taken by certain .-dimensional random vectors {..…, ..}. The proper framework in which to study time series is that of stochastic processes.
埋伏
发表于 2025-3-25 18:44:17
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Proponent
发表于 2025-3-25 21:38:27
Multivariate Structural Models,Multivariate structural models are defined in a way similar to that of univariate structural models, described in Sect. .. For example, let the stochastic vector .. satisfy .. = .. + .. + .., where .. is the trend, .. is the seasonal, and .. is the irregular component.
GOAT
发表于 2025-3-26 03:00:11
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窗帘等
发表于 2025-3-26 04:47:34
The State Space Model,The state space model considered in SSMMATLAB is . where {..} is a multivariate process with ., .., .., .., .., .., and .. are time-varying deterministic matrices, . is a constant bias vector, . is the state vector, and {..} is a sequence of uncorrelated stochastic vectors, ., with zero mean and common covariance matrix ...
Bmd955
发表于 2025-3-26 12:27:12
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现任者
发表于 2025-3-26 14:30:55
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Innovative
发表于 2025-3-26 18:44:52
Statistics and Computinghttp://image.papertrans.cn/l/image/586432.jpg