Time Series Modeling with MATLAB: The SSpace Toolbox

Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)


SSpace is a MATLAB toolbox for State-Space modeling that provides the user with tools for linear Gaussian, nonlinear, and non-Gaussian systems with the most advanced and up-to-date features available in any State-Space framework. Great flexibility is achieved because each model is coded on a standard MATLAB function, thence having absolute control on particular parameterizations, parameter constraints, time variation of parameters or variances, arbitrary nonlinear relations with inputs, time aggregation, nested models, system concatenation, etc. The toolbox may be used by specifying State-Space systems from scratch or by using ready-to-use templates for standard methods (like VARMAX, exponential smoothing, unobserved components, Dynamic Linear Regression, etc.). The toolbox is freely available via a public code repository with full documentation and help system. This chapter demonstrates the toolbox’s potential with several examples.


MATLAB State-Space systems Kalman filter Smoother algorithm Maximum likelihood 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Industrial Engineering PolitecnicUniversity of Castilla-La ManchaCiudad RealSpain
  2. 2.Faculty of Chemical Sciences and TechnologiesUniversity of Castilla-La ManchaCiudad RealSpain

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