Bridging the Gap Between Ox and Gauss using OxGauss
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- Jean-Pierre Urbain & Sébastien Laurent, 2005. "Bridging the gap between Ox and Gauss using OxGauss," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 131-139.
- LAURENT, Sébastien & URBAIN, Jean-Pierre, 2004. "Bridging the gap between Ox and Gauss using OxGauss," CORE Discussion Papers 2004012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
References listed on IDEAS
- Franses,Philip Hans & Dijk,Dick van, 2000.
"Non-Linear Time Series Models in Empirical Finance,"
Cambridge University Press, number 9780521770415.
- Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
- Laurent, Sebastien & Peters, Jean-Philippe, 2002. " G@RCH 2.2: An Ox Package for Estimating and Forecasting Various ARCH Models," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 447-485, July.
- Francisco Cribari-Neto & Spyros Zarkos, 2003. "Econometric and Statistical Computing Using Ox," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 277-295, June.
- Cribari-Neto, Francisco, 1997. "Econometric Programming Environments: GAUSS, Ox and S-PLUS," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(1), pages 77-89, Jan.-Feb..
- Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, January.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Benoit Bellone, 2005. "Classical Estimation of Multivariate Markov-Switching Models using MSVARlib," Econometrics 0508017, EconWPA.
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NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-CMP-2004-04-18 (Computational Economics)
- NEP-ECM-2004-03-28 (Econometrics)
- NEP-ETS-2004-03-28 (Econometric Time Series)
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