Autoregressive moving-average model: Difference between revisions

Revision as of 15:18, 1 October 2024

Revision as of 15:27, 1 October 2024

Line 93:

=== Implementations in statistics packages ===

* In [[R (programming language)|R]], thestandard package <code>arimastats</code> has function (in standard package <code>statsarima</code>) is, documented in [http://search.r-project.org/R/library/stats/html/arima.html ARIMA Modelling of Time Series]. The packagePackage [https://cran.r-project.org/web/packages/astsa/index.html <code>astsa</code>] has an improved script called <code>sarima</code> for fitting ARMA models (seasonal and nonseasonal) as well asand <code>sarima.sim</code> to simulate data from these models. Extension packages contain related and extended functionality,: e.g., thepackage <code>tseries</code> package includes anthe function <code>arma()</code> function, documented in [http://finzi.psych.upenn.edu/R/library/tseries/html/arma.html "Fit ARMA Models to Time Series"]; the package[https://cran.r-project.org/web/packages/fracdiff <code>fracdiff</code> package] contains <code>fracdiff()</code> for fractionally integrated ARMA processes; and thepackage [https://cran.r-project.org/web/packages/forecast/index.html <code>forecast package</code>] includes <code>auto.arima</code> for selecting a parsimonious set of ''p, q''. The CRAN task view on [https://cran.r-project.org/web/views/TimeSeries.html Time Series] contains links to most of these.

* [[Mathematica]] has a complete library of time series functions including ARMA.<ref>[http://www.wolfram.com/products/applications/timeseries/features.html Time series features in Mathematica] {{webarchive |url=https://web.archive.org/web/20111124032002/http://www.wolfram.com/products/applications/timeseries/features.html |date=November 24, 2011 }}</ref>

* [[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, 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 more informationdetails.

* [[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>[http://statsmodels.sourceforge.net/ moduleS] 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]]. [http://statsmodels.sourceforge.net/ See details].

* [[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]] can estimate AR models using functions from the extra package [http://octave.sourceforge.net/ <code>octave-forge</code>] supports AR models.

* [[Stata]] includes the function <code>arima</code>. which can estimatefor ARMA and [[Autoregressive integrated moving average|ARIMA]] models. [https://www.stata.com/help.cgi?arima. See here for more details].

* [[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"].

* [[SAS (software)|SAS]] has an econometric package, ETS, that estimates ARIMA models. [https://web.archive.org/web/20110930032431/http://support.sas.com/rnd/app/ets/proc/ets_arima.html See details].