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Statistical algorithms for models in state space form using SsfPack 2.2.

Опубликовано на портале: 07-04-2004
Econometrics Journal. 1999.  Vol. 2. No. 1. P. 107-160. 
Тематический раздел:
The paper discusses and documents the algorithms of SsfPack 2.2. SsfPack is a suite of C routines for carrying out computations involving the statistical analysis of univariate models in state space form. The emphasis is on documenting the link we have made to the Ox computing environment. SsfPack allows for a full range of different state space forms: from a simple time-invariant model to a complicated time-varying model. Functions can be used which put standart models such as ARMA and cubic spline models in state space form. Basic functions are available for filtering, moment smoothing and simulation smoothing. Ready-to-use functions are provided for standart tasks such as likelihood evaluation, forecasting and signal extraction. They shows that SsfPack can be easily used for implementing, fitting and analysing Gaussian models relevant to many areas of econometrics and statistics. Some Gaussian illustrations are given.

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