Autoregressive moving-average model: Difference between revisions

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* [[MATLAB]] includes functions such as [http://www.mathworks.com/help/econ/arma-model.html <code>arma</code>], [http://www.mathworks.com/help/ident/ref/ar.html <code>ar</code>] and [http://www.mathworks.com/help/ident/ref/arx.html <code>arx</code>] to estimate autoregressive, exogenous autoregressive and ARMAX models. See [http://www.mathworks.com/help/ident/ug/estimating-ar-and-arma-models.html System Identification Toolbox] and [http://www.mathworks.com/help/econ/arima.estimate.html Econometrics Toolbox] for details.
* [[Julia_(programming_language) | Julia]] has community-driven packages that implement fitting with an ARMA model such as [https://github.com/joefowler/ARMA.jl <code>arma.jl</code>].
* Python has the <code>statsmodels</code>[httphttps://statsmodels.sourceforge.net/ S] package which includes many models and functions for time series analysis, including ARMA. Formerly part of the [[scikit-learn]] library, it is now stand-alone and integrates well with [[Pandas (software)|Pandas]].
* [[PyFlux]] has a Python-based implementation of ARIMAX models, including Bayesian ARIMAX models.
* [[IMSL Numerical Libraries]] are libraries of numerical analysis functionality including ARMA and ARIMA procedures implemented in standard programming languages like C, Java, C# .NET, and Fortran.
* [[gretl]] can estimate ARMA models, as mentioned [http://constantdream.wordpress.com/2008/03/16/gnu-regression-econometrics-and-time-series-library-gretl/ here]
* [[GNU Octave]] extra package [httphttps://octave.sourceforge.net/ <code>octave-forge</code>] supports AR models.
* [[Stata]] includes the function <code>arima</code>. for ARMA and [[Autoregressive integrated moving average|ARIMA]] models.
* [[SuanShu]] is a Java library of numerical methods that implements univariate/multivariate ARMA, ARIMA, ARMAX, etc models, documented in [http://www.numericalmethod.com/javadoc/suanshu/ "SuanShu, a Java numerical and statistical library"].