Statistical Algorithms for Models in State Space Form: SsfPack 3.0. - Koopman, S; Shephard, N; Doornik, J (Timberlake Consultants Ltd, 2008)
SsfPack™ (Extended) version 3.0 is a suite of C routines for carrying out computations involving the statistical analysis of univariate and multivariate models in state space form with easy-to-use functions for Ox. SsfPack requires Ox 4 or above to run. SsfPack allows for a full range of different state space forms: from a simple time-invariant model to a complicated multivariate time-varying model. Functions are provided to put standard models such as SARIMA, unobserved components, time-varying regressions and cubic spline models into state space form. Basic functions are available for filtering, moment smoothing and simulation smoothing. Ready-to-use functions are provided for standard tasks such as likelihood evaluation, forecasting and signal extraction. SsfPack can be used for implementing, fitting and analysing Gaussian models relevant to many areas of econometrics and statistics. It provides all relevant tools for the treatment of non-Gaussian and nonlinear state space models. In particular, tools are available to implement simulation based estimation methods such as importance sampling and Markov chain Monte Carlo (MCMC) methods.