Editing Autoregressive model (section)

==Implementations in statistics packages==
* [[R (programming language)|R]] – the ''stats'' package includes ''ar'' function;<ref>[http://finzi.psych.upenn.edu/R/library/stats/html/ar.html "Fit Autoregressive Models to Time Series"] {{Webarchive|url=https://web.archive.org/web/20160128234632/http://finzi.psych.upenn.edu/R/library/stats/html/ar.html |date=2016-01-28}} (in R)</ref> the ''astsa'' package includes ''sarima'' function to fit various models including AR.<ref name=":0">{{Cite web |last1=Stoffer |first1=David |last2=Poison |first2=Nicky |date=2023-01-09 |title=astsa: Applied Statistical Time Series Analysis |url=https://cran.r-project.org/web/packages/astsa/ |access-date=2023-08-20}}</ref>
* [[MATLAB]] – the Econometrics Toolbox<ref>{{Cite web |url=https://www.mathworks.com/products/econometrics.html |title=Econometrics Toolbox |website=www.mathworks.com |access-date=2022-02-16 |archive-date=2023-04-16 |archive-url=https://web.archive.org/web/20230416160907/https://www.mathworks.com/products/econometrics.html |url-status=live}}</ref> and System Identification Toolbox<ref>{{Cite web |url=https://www.mathworks.com/products/sysid.html |title=System Identification Toolbox |website=www.mathworks.com |access-date=2022-02-16 |archive-date=2022-02-16 |archive-url=https://web.archive.org/web/20220216063519/https://www.mathworks.com/products/sysid.html |url-status=live}}</ref> include AR models.<ref>{{Cite web |url=https://www.mathworks.com/help/econ/autoregressive-model.html |title=Autoregressive Model - MATLAB & Simulink |website=www.mathworks.com |access-date=2022-02-16 |archive-date=2022-02-16 |archive-url=https://web.archive.org/web/20220216063648/https://www.mathworks.com/help/econ/autoregressive-model.html |url-status=live}}</ref>
* [[MATLAB]] and [[GNU Octave|Octave]] – the ''TSA'' toolbox contains several estimation functions for uni-variate, [[multivariate statistics|multivariate]], and adaptive AR models.<ref>{{Cite web |url=http://pub.ist.ac.at/~schloegl/matlab/tsa/ |title=The Time Series Analysis (TSA) toolbox for Octave and MATLAB |website=pub.ist.ac.at |access-date=2012-04-03 |archive-date=2012-05-11 |archive-url=https://web.archive.org/web/20120511144225/http://pub.ist.ac.at/~schloegl/matlab/tsa/ |url-status=live}}</ref>
* [[PyMC]]3 – the Bayesian statistics and probabilistic programming framework supports AR modes with ''p'' lags.
* ''bayesloop'' – supports parameter inference and model selection for the AR-1 process with time-varying parameters.<ref>{{Cite web |url=https://github.com/christophmark/bayesloop |title=christophmark/bayesloop |date=December 7, 2021 |via=GitHub |access-date=September 4, 2018 |archive-date=September 28, 2020 |archive-url=https://web.archive.org/web/20200928085417/https://github.com/christophmark/bayesloop |url-status=live}}</ref>
*[[Python (programming language)|Python]] – statsmodels.org hosts an AR model.<ref>{{Cite web |url=https://www.statsmodels.org/stable/generated/statsmodels.tsa.ar_model.AutoReg.html |title=statsmodels.tsa.ar_model.AutoReg — statsmodels 0.12.2 documentation |website=www.statsmodels.org |access-date=2021-04-29 |archive-date=2021-02-28 |archive-url=https://web.archive.org/web/20210228123354/https://www.statsmodels.org/stable/generated/statsmodels.tsa.ar_model.AutoReg.html |url-status=live}}</ref>