GAUSS

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 109 articles )

Showing results 1 to 20 of 109.
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  1. Chow, Sy-Miin; Ou, Lu; Ciptadi, Arridhana; Prince, Emily B.; You, Dongjun; Hunter, Michael D.; Rehg, James M.; Rozga, Agata; Messinger, Daniel S.: Representing sudden shifts in intensive dyadic interaction data using differential equation models with regime switching (2018)
  2. Giovanni Millo: Robust Standard Error Estimators for Panel Models: A Unifying Approach (2017)
  3. Marek Hlavac: ExtremeBounds: Extreme Bounds Analysis in R (2016)
  4. Pek, Jolynn; Wu, Hao: Profile likelihood-based confidence intervals and regions for structural equation models (2015)
  5. Roger Bivand; Gianfranco Piras: Comparing Implementations of Estimation Methods for Spatial Econometrics (2015)
  6. Victor Gómez: SSMMATLAB: A Set of MATLAB Programs for the Statistical Analysis of State Space Models (2015)
  7. Brenton Kenkel; Curtis Signorino: Estimating Extensive Form Games in R (2014)
  8. Haines, Linda M.; Clark, Allan E.: The construction of optimal designs for dose-escalation studies (2014)
  9. Peter Ruckdeschel; Matthias Kohl: General Purpose Convolution Algorithm in S4 Classes by Means of FFT (2014)
  10. Ringle, Christian M.; Sarstedt, Marko; Schlittgen, Rainer: Genetic algorithm segmentation in partial least squares structural equation modeling (2014)
  11. Chow, Sy-Miin; Zhang, Guangjian: Nonlinear regime-switching state-space (RSSS) models (2013)
  12. Martin, Vance; Hurn, Stan; Harris, David: Econometric modelling with time series. Specification, estimation and testing (2013)
  13. Yu, Jun-Wu; Tian, Guo-Liang: Efficient algorithms for generating truncated multivariate normal distributions (2011)
  14. Cai, Li: High-dimensional exploratory item factor analysis by a Metropolis-Hastings Robbins-Monro algorithm (2010)
  15. de Grange, Louis; Fernández, Enrique; de Cea, Joaquín; Irrazábal, Magdalena: Combined model calibration and spatial aggregation (2010)
  16. Marcelo Almiron; Bruno Lopes; Alyson Oliveira; Antonio Medeiros; Alejandro Frery: On the Numerical Accuracy of Spreadsheets (2010)
  17. Pierre Chaussé: Computing Generalized Method of Moments and Generalized Empirical Likelihood with R (2010)
  18. Ulrike Grömping: Inference with Linear Equality and Inequality Constraints Using R: The Package ic.infer (2010)
  19. Yalta, A. Talha; Yalta, A. Yasemin: Should economists use open source software for doing research? (2010) ioport
  20. Yang, Manshu; Chow, Sy-Miin: Using state-space model with regime switching to represent the dynamics of facial electromyography (EMG) data (2010)

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