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 493 articles )

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  1. Gonçalves, Flávio B.; Dutra, Lívia M.; Silva, Roger W. C.: Exact and computationally efficient Bayesian inference for generalized Markov modulated Poisson processes (2022)
  2. Irie, Kaoru; Glynn, Chris; Aktekin, Tevfik: Sequential modeling, monitoring, and forecasting of streaming web traffic data (2022)
  3. Lemonte, Artur J.: Covariance matrix of maximum likelihood estimators in censored exponential regression models (2022)
  4. Cavalcanti, Alexsandro B.; Botter, Denise A.; Barroso, Lúcia P.; Santos-Neto, Manoel; Cordeiro, Gauss M.: Improved score tests for exponential family nonlinear models (2021)
  5. Chakraborty, Subrata; Chakravarty, Dhrubajyoti; Mazucheli, Josmar; Bertoli, Wesley: A discrete analog of Gumbel distribution: properties, parameter estimation and applications (2021)
  6. Karamikabir, Hamid; Afshari, Mahmoud; Alizadeh, Morad; Hamedani, G. G.: A new extended generalized Gompertz distribution with statistical properties and simulations (2021)
  7. Kubokawa, T.; Sugasawa, S.; Tamae, H.; Chaudhuri, S.: General unbiased estimating equations for variance components in linear mixed models (2021)
  8. Medeiros, Francisco M. C.; Lemonte, Artur J.: Likelihood-based inference in censored exponential regression models (2021)
  9. Morita, Lia H. M.; Tomazella, Vera L. D.; Ramos, Pedro L.; Ferreira, Paulo H.; Louzada, Francisco: The random deterioration rate model with measurement error based on the inverse Gaussian distribution (2021)
  10. Pinheiro, Eliane C.; Ferrari, Silvia L. P.; Medeiros, Francisco M. C.: Higher-order approximate confidence intervals (2021)
  11. Araújo, Mariana C.; Cysneiros, Audrey H. M. A.; Montenegro, Lourdes C.: Improved heteroskedasticity likelihood ratio tests in symmetric nonlinear regression models (2020)
  12. Castellares, Fredy; Lemonte, Artur J.; Moreno-Arenas, Germán: On the two-parameter Bell-Touchard discrete distribution (2020)
  13. Guedes, Ana C.; Cribari-Neto, Francisco; Espinheira, Patrícia L.: Modified likelihood ratio tests for unit gamma regressions (2020)
  14. Kunihama, Tsuyoshi; Li, Zehang Richard; Clark, Samuel J.; Mccormick, Tyler H.: Bayesian factor models for probabilistic cause of death assessment with verbal autopsies (2020)
  15. Kurita, Takamitsu: Normalising cointegrating relationships subject to long-run exclusion (2020)
  16. Kurita, Takamitsu: Likelihood-based tests for parameter constancy in (I(2)) CVAR models with an application to fixed-term deposit data (2020)
  17. Lemonte, Artur J.; Moreno-Arenas, Germán: On a heavy-tailed parametric quantile regression model for limited range response variables (2020)
  18. Lemonte, Artur J.; Moreno-Arenas, Germán: Improved estimation for a new class of parametric link functions in binary regression (2020)
  19. Li, Mengheng; Koopman, Siem Jan; Lit, Rutger; Petrova, Desislava: Long-term forecasting of El Niño events via dynamic factor simulations (2020)
  20. Mazucheli, Josmar; Bertoli, Wesley; Oliveira, Ricardo P.; Menezes, André F. B.: On the discrete quasi xgamma distribution (2020)

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