Abstract
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. The routines allow for a variety of state space forms from simple time invariant models to complicated time-varying models. Functions are available to put standard models like ARMA and spline models in state space form. General routines are available for filtering, smoothing, simulation smoothing, likelihood evaluation, forecasting and signal extraction. Full details of the statistical analysis is provided in Durbin and Koopman (2001). This chapter gives an overview of state space modeling and the reader is referred to the papers by Koopman, Shephard and Doornik for technical details on the algorithms used in the S+FinMetrics/SsfPack functions.
Information about Ssfpack can be found at http://www.ssfpack.com.
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14.6 References
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(2006). State Space Models. In: Modeling Financial Time Series with S-PLUS®. Springer, New York, NY. https://doi.org/10.1007/978-0-387-32348-0_14
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DOI: https://doi.org/10.1007/978-0-387-32348-0_14
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