Statistics Inference for stochastic processes and time series Concept
Autoregressive model
Summary
An autoregressive model describes each value of a time series as a linear combination of a few past values plus a random shock. The number of past values used is the order , and the model is written AR(). It is one of the simplest and most used models for dependent data, and a building block of ARMA and ARIMA models.
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| Tag | 2JC96FMGA1 |
|---|---|
| URI | m2://2JC96FMGA1 |
| Kind | concept |
| Writing | W0 stub |
| MSC | 62M10, 91B84 |
| Same as |
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Used by
- Autoregressive–moving-average model
- Yule–Walker equations
- Dickey–Fuller test
- Moving-average model
- Partial autocorrelation function