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State Space Methods in gretl

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  • Lucchetti, Riccardo

Abstract

gretl is a general-purpose econometric package, whose most important characteristic is being free software. This ensures that its source code is freely available under the general public license (GPL) and, like most GPL software, that it can be used free of charge. As of version 1.8.1 (released in May 2009), it offers a mechanism for handling linear state space models in a reasonably general and efficient way. This article illustrates its main features with two examples.

Suggested Citation

  • Lucchetti, Riccardo, 2011. "State Space Methods in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i11).
  • Handle: RePEc:jss:jstsof:v:041:i11
    DOI: http://hdl.handle.net/10.18637/jss.v041.i11
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    References listed on IDEAS

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    1. RUSSO, Giuseppe & VEREDAS, David, 2000. "Institutional rigidities and employment rigidity in the Italian large industrial firms," LIDAM Discussion Papers CORE 2000048, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. A. Talha Yalta & Riccardo Lucchetti, 2008. "The GNU|Linux platform and freedom respecting software for economists," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 279-286.
    3. Riccardo Lucchetti, 2009. "Who uses gretl? An Analysis of the SourceForge Download Data," EHUCHAPS, in: Ignacio Díaz-Emparanza & Petr Mariel & María Victoria Esteban (ed.), Econometrics with gretl. Proceedings of the gretl Conference 2009, edition 1, chapter 3, pages 45-55, Universidad del País Vasco - Facultad de Ciencias Económicas y Empresariales.
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    Cited by:

    1. Gómez, Victor, 2015. "SSMMATLAB: A Set of MATLAB Programs for the Statistical Analysis of State Space Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 66(i09).
    2. Błażejowski, Marcin & Kwiatkowski, Jacek, 2015. "Bayesian Model Averaging and Jointness Measures for gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(i05).
    3. Commandeur, Jacques J. F. & Koopman, Siem Jan & Ooms, Marius, 2011. "Statistical Software for State Space Methods," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i01).
    4. Chirico, Paolo, 2014. "Modelli strutturali e Filtri di Kalman per serie storiche univariate. Teoria ed applicazioni con Gretl," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201401, University of Turin.
    5. Yalta, A. Talha & Schreiber, Sven, 2012. "Random Number Generation in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 50(c01).
    6. Allin Cottrell & Riccardo (Jack) Lucchetti & Matteo Pelagatti, 2016. "Measures of variance for smoothed disturbances in linear state-space models: a clarification," gretl working papers 3, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    7. Marcin Błażejowski, 2024. "Which C compiler and BLAS/LAPACK library should I use: gretl’s numerical efficiency in different configurations," Computational Statistics, Springer, vol. 39(7), pages 3497-3522, December.
    8. Riccardo “Jack” Lucchetti & Francesco Valentini, 2024. "Linear models with time-varying parameters: a comparison of different approaches," Computational Statistics, Springer, vol. 39(7), pages 3523-3545, December.

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