Ox is an object-oriented matrix programming language with a comprehensive mathematical and statistical function library. Matrices can be used directly in expressions, for example to multiply two matrices, or to invert a matrix. The major features of Ox are its speed, extensive library, and well-designed syntax, which leads to programs which are easier to maintain. For a first impression of the matrix and statistical function library see the Function summary. Versions of Ox are available for many platforms.

References in zbMATH (referenced in 345 articles )

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  1. Darolles, Serge; Francq, Christian; Laurent, Sébastien: Asymptotics of Cholesky GARCH models and time-varying conditional betas (2018)
  2. Imaizumi, Masaaki; Kato, Kengo: PCA-based estimation for functional linear regression with functional responses (2018)
  3. Bourguignon, Marcelo; Leão, Jeremias; Leiva, Víctor; Santos-Neto, Manoel: The transmuted Birnbaum-Saunders distribution (2017)
  4. Cavaliere, Giuseppe; Nielsen, Heino Bohn; Rahbek, Anders: On the consistency of bootstrap testing for a parameter on the boundary of the parameter space (2017)
  5. da Silva Braga, Altemir; Cordeiro, Gauss M.; Ortega, Edwin M.M.; Silva, Giovana O.: The odd log-logistic Student $t$ distribution: theory and applications (2017)
  6. Espinheira, Patrícia L.; Santos, Evelyne G.; Cribari-Neto, Francisco: On nonlinear beta regression residuals (2017)
  7. Mirmostafaee, S.M.T.K.; Mahdizadeh, M.; Lemonte, Artur J.: The Marshall-Olkin extended generalized Rayleigh distribution: properties and applications (2017)
  8. Rezaei, Sadegh; Sadr, Behnam Bahrami; Alizadeh, Morad; Nadarajah, Saralees: Topp-Leone generated family of distributions: properties and applications (2017)
  9. Santos, Cristiano C.; Loschi, Rosangela H.: Maximum likelihood estimation and parameter interpretation in elliptical mixed logistic regression (2017)
  10. Zheng, Tingguo; Chen, Rong: Dirichlet ARMA models for compositional time series (2017)
  11. Ann George and Alexander Robitzsch and Thomas Kiefer and Jürgen Groß and Ali Ünlü: The R Package CDM for Cognitive Diagnosis Models (2016)
  12. Bollerslev, Tim; Patton, Andrew J.; Quaedvlieg, Rogier: Exploiting the errors: a simple approach for improved volatility forecasting (2016)
  13. Castellares, Fredy; Lemonte, Artur J.: On the Marshall-Olkin extended distributions (2016)
  14. Cordeiro, Gauss M.; Silva, Giovana O.; Ortega, Edwin M.M.: An extended-G geometric family (2016)
  15. de la Torre, Jimmy; Chiu, Chia-Yi: A general method of empirical Q-matrix validation (2016)
  16. Dias, Cícero R.B.; Cordeiro, Gauss M.; Alizadeh, Morad; Diniz Marinho, Pedro Rafael; Campos Co^elho, Hemílio Fernandes: Exponentiated Marshall-Olkin family of distributions (2016)
  17. Doornik, Jurgen A.: An example of instability: Discussion of the paper by S\orenJohansen and Bent Nielsen (2016)
  18. Doornik, Jurgen A.; Hendry, David F.: Outliers and model selection: Discussion of the paper by S\orenJohansen and Bent Nielsen (2016)
  19. Hasegawa, Hikaru; Ueda, Kazuhiro: Multidimensional inequality for current status of Japanese private companies’ employees (2016)
  20. Hong, Chen-Yu; Chang, Yu-Wei; Tsai, Rung-Ching: Estimation of generalized DINA model with order restrictions (2016)

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