Ox

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 202 articles )

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  1. Bollerslev, Tim; Patton, Andrew J.; Quaedvlieg, Rogier: Exploiting the errors: a simple approach for improved volatility forecasting (2016)
  2. Cordeiro, Gauss M.; Silva, Giovana O.; Ortega, Edwin M.M.: An extended-G geometric family (2016)
  3. de la Torre, Jimmy; Chiu, Chia-Yi: A general method of empirical Q-matrix validation (2016)
  4. Kobayashi, Genya: Skew exponential power stochastic volatility model for analysis of skewness, non-normal tails, quantiles and expectiles (2016)
  5. Lanjoni, Beatriz R.; Ortega, Edwin M.M.; Cordeiro, Gauss M.: Extended Burr XII regression models: theory and applications (2016)
  6. Leão, Jeremias; Cysneiros, Francisco; Saulo, Helton; Balakrishnan, N.: Constrained test in linear models with multivariate power exponential distribution (2016)
  7. Alizadeh, Morad; Cordeiro, Gauss M.; de Brito, Edleide; Demétrio, Clarice Garcia B.: The beta Marshall-Olkin family of distributions (2015)
  8. Alizadeh, Morad; Tahir, M.H.; Cordeiro, Gauss M.; Mansoor, M.; Zubair, M.; Hamedani, G.G.: The Kumaraswamy Marshal-Olkin family of distributions (2015)
  9. Bayer, Fábio M.; Cribari-Neto, Francisco: Bootstrap-based model selection criteria for beta regressions (2015)
  10. Boswijk, H.Peter; Jansson, Michael; Nielsen, Morten Ørregaard: Improved likelihood ratio tests for cointegration rank in the VAR model (2015)
  11. Cavaliere, Giuseppe; Nielsen, Morten Ørregaard; Taylor, A.M.Robert: Bootstrap score tests for fractional integration in heteroskedastic ARFIMA models, with an application to price dynamics in commodity spot and futures markets (2015)
  12. de Castro, Mário; Galea, Manuel: Inference in a structural heteroskedastic calibration model (2015)
  13. Doornik, Jurgen A.: Numerical evaluation of the Gauss hypergeometric function by power summations (2015)
  14. Hashimoto, Elizabeth M.; Ortega, Edwin M.M.; Cordeiro, Gauss M.; Cancho, Vicente G.: A new long-term survival model with interval-censored data (2015)
  15. Huo, Yan; de la Torre, Jimmy; Mun, Eun-Young; Kim, Su-Young; Ray, Anne E.; Jiao, Yang; White, Helene R.: A hierarchical multi-unidimensional IRT approach for analyzing sparse, multi-group data for integrative data analysis (2015)
  16. Xiao, Yuewen; Ku, Yu-Cheng; Bloomfield, Peter; Ghosh, Sujit K.: On the degrees of freedom in MCMC-based Wishart models for time series data (2015)
  17. Borges, Patrick; Rodrigues, Josemar; Balakrishnan, Narayanaswamy; Bazán, Jorge: A COM-Poisson type generalization of the binomial distribution and its properties and applications (2014)
  18. Castle, Jennifer L.; Hendry, David F.: Model selection in under-specified equations facing breaks (2014)
  19. Cordeiro, Gauss M.; Botter, Denise A.; Cavalcanti, Alexsandro B.; Barroso, Lúcia P.: Covariance matrix of the bias-corrected maximum likelihood estimator in generalized linear models (2014)
  20. Cordeiro, Gauss M.; Lemonte, Artur J.: The exponentiated generalized Birnbaum-Saunders distribution (2014)

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