The GAUSS Mathematical and Statistical System is a fast matrix programming language widely used by scientists, engineers, statisticians, biometricians, econometricians, and financial analysts. Designed for computationally intensive tasks, the GAUSS system is ideally suited for the researcher who does not have the time required to develop programs in C/C++ or FORTRAN but finds that most statistical or mathematical “packages” are not flexible or powerful enough to perform complicated analysis or to work on large problems. Whatever mathematical tool or language you are now using, you’ll find that GAUSS can greatly increase your productivity!

This software is also referenced in ORMS.

References in zbMATH (referenced in 41 articles )

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  1. Pek, Jolynn; Wu, Hao: Profile likelihood-based confidence intervals and regions for structural equation models (2015)
  2. Ringle, Christian M.; Sarstedt, Marko; Schlittgen, Rainer: Genetic algorithm segmentation in partial least squares structural equation modeling (2014)
  3. Martin, Vance; Hurn, Stan; Harris, David: Econometric modelling with time series. Specification, estimation and testing (2013)
  4. Yu, Jun-Wu; Tian, Guo-Liang: Efficient algorithms for generating truncated multivariate normal distributions (2011)
  5. Yalta, A.Talha; Yalta, A.Yasemin: Should economists use open source software for doing research? (2010) ioport
  6. Ajmani, Vivek B.: Applied econometrics using the SAS system (2009)
  7. Almiron, Marcelo G.; Almeida, Eliana S.; Miranda, Marcio N.: The reliability of statistical functions in four software packages freely used in numerical computation (2009)
  8. McCullough, B.D.: Special section on Microsoft Excel 2007 (2008)
  9. McCullough, B.D.; Heiser, David A.: On the accuracy of statistical procedures in Microsoft Excel 2007 (2008)
  10. Yalta, A.Talha: The accuracy of statistical distributions in Microsoft$^\circledR$ Excel 2007 (2008)
  11. Bhowmik, Jahar L.; King, Maxwell L.: Maximal invariant likelihood based testing of semi-linear models (2007)
  12. Begum, Nelufa; King, Maxwell L.: Most mean powerful test of a composite null against a composite alternative (2005)
  13. Lütkepohl, Helmut: New introduction to multiple time series analysis. (2005)
  14. Borkowf, Craig B.: An efficient algorithm for generating two-way contingency tables with fixed marginal totals and arbitrary mean proportions, with applications to permutation tests (2003)
  15. Borkowf, Craig B.: Computing the nonnull asymptotic variance and the asymptotic relative efficiency of Spearman’s rank correlation (2002)
  16. Ramakrishnan, Naren; Rice, John R.; Houstis, Elias N.: GAUSS: an online algorithm selection system for numerical quadrature (2002)
  17. Hager, Manfred; Neck, Reinhard; Behrens, Doris A.: Solving dynamic macroeconomic policy games using the algorithm OPTGAME 1.0 (2001)
  18. Müller, Werner G.: Collecting spatial data. Optimum design of experiments for random fields. (2001)
  19. Mittelhammer, Ron C.; Judge, George G.; Miller, Douglas J.: Econometric foundations. With 1 CD-ROM (Windows 95, 98, NT) (2000)
  20. Verbeek, Marno: A guide to modern econometrics (2000)

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