Econometric and Statistical Computing Using Ox
AbstractThis paper reviews the matrix programminglanguage Ox from the viewpoint of an econometrician/statistician.We focus on scientific programming using Ox and discussexamples of possible interest to econometricians and statisticians, such as random number generation, maximum likelihood estimation, andMonte Carlo simulation. Ox is a remarkable matrix programming language which is well suited to research and teaching in econometrics and statistics. Copyright Kluwer Academic Publishers 2003
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Bibliographic InfoArticle provided by Society for Computational Economics in its journal Computational Economics.
Volume (Year): 21 (2003)
Issue (Month): 3 (June)
C programming language; graphics; matrix programming language; maximum likelihood estimation; Monte Carlo simulation; Ox ;
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- Podivinsky, Jan M, 1999. " Ox 2.10: Beast of Burden or Object of Desire?," Journal of Economic Surveys, Wiley Blackwell, vol. 13(4), pages 491-502, September.
- Hans M. Amman & David A. Kendrick, 1995.
"Programming Languages in Economics,"
CARE Working Papers
9504, The University of Texas at Austin, Center for Applied Research in Economics.
- Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999.
"Statistical algorithms for models in state space using SsfPack 2.2,"
Royal Economic Society, vol. 2(1), pages 107-160.
- Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998. "Statistical Algorithms for Models in State Space Using SsfPack 2.2," Discussion Paper 1998-141, Tilburg University, Center for Economic Research.
- Marius Ooms, 1999. "Review of SsfPack 2.2: statistical algorithms for models in state space," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 161-166.
- S»bastien Laurent and Jean-Philippe Peters, 2001. "G@RCH 2.0: An Ox Package for Estimating and Forecasting Various ARCH Models," Computing in Economics and Finance 2001 123, Society for Computational Economics.
- MacKinnon, James G, 1999. "The Linux Operating System: Debian GNU/Linux," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(4), pages 443-52, July-Aug..
- 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).
- Urbain,Jean-Pierre & Laurent,Sébastien, 2004. "Bridging the Gap Between Ox and Gauss using OxGauss," Research Memoranda 007, Maastricht : METEOR, Maastricht Research School of Economics of Technology and Organization.
- Lemonte, Artur J. & Cribari-Neto, Francisco & Vasconcellos, Klaus L.P., 2007. "Improved statistical inference for the two-parameter Birnbaum-Saunders distribution," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4656-4681, May.
- Barreto-Souza, Wagner & Cribari-Neto, Francisco, 2009. "A generalization of the exponential-Poisson distribution," Statistics & Probability Letters, Elsevier, vol. 79(24), pages 2493-2500, December.
- Melo, Tatiane F.N. & Ferrari, Silvia L.P. & Cribari-Neto, Francisco, 2009. "Improved testing inference in mixed linear models," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2573-2582, May.
- Achim Zeileis, . "Econometric Computing with HC and HAC Covariance Matrix Estimators," Journal of Statistical Software, American Statistical Association, vol. 11(i10).
- Ospina, Raydonal & Cribari-Neto, Francisco & Vasconcellos, Klaus L.P., 2006. "Improved point and interval estimation for a beta regression model," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 960-981, November.
- Lemonte, Artur J. & Ferrari, Silvia L.P. & Cribari-Neto, Francisco, 2010. "Improved likelihood inference in Birnbaum-Saunders regressions," Computational Statistics & Data Analysis, Elsevier, vol. 54(5), pages 1307-1316, May.
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