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  2. Autoregressive moving-average model - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_moving...

    For example, processes in the AR(1) model with | | are not stationary because the root of = lies within the unit circle. [3] The augmented Dickey–Fuller test assesses the stability of IMF and trend components. For stationary time series, the ARMA model is used, while for non-stationary series, LSTM models are used to derive abstract features.

  3. Autoregressive integrated moving average - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_integrated...

    In time series analysis used in statistics and econometrics, autoregressive integrated moving average (ARIMA) and seasonal ARIMA (SARIMA) models are generalizations of the autoregressive moving average (ARMA) model to non-stationary series and periodic variation, respectively.

  4. In an ARIMA model, the integrated part of the model includes the differencing operator (1 − B) (where B is the backshift operator) raised to an integer power.For example,

  5. Box–Jenkins method - Wikipedia

    en.wikipedia.org/wiki/Box–Jenkins_method

    For example, for monthly data one would typically include either a seasonal AR 12 term or a seasonal MA 12 term. For Box–Jenkins models, one does not explicitly remove seasonality before fitting the model. Instead, one includes the order of the seasonal terms in the model specification to the ARIMA estimation software. However, it may be ...

  6. Moving-average model - Wikipedia

    en.wikipedia.org/wiki/Moving-average_model

    [1] [2] The moving-average model specifies that the output variable is cross-correlated with a non-identical to itself random-variable. Together with the autoregressive (AR) model, the moving-average model is a special case and key component of the more general ARMA and ARIMA models of time series, [3] which have a more complicated stochastic ...

  7. X-13ARIMA-SEATS - Wikipedia

    en.wikipedia.org/wiki/X-13ARIMA-SEATS

    X-13ARIMA-SEATS, successor to X-12-ARIMA and X-11, is a set of statistical methods for seasonal adjustment and other descriptive analysis of time series data that are implemented in the U.S. Census Bureau's software package. [3]

  8. Partial autocorrelation function - Wikipedia

    en.wikipedia.org/wiki/Partial_autocorrelation...

    Partial autocorrelation is a commonly used tool for identifying the order of an autoregressive model. [6] As previously mentioned, the partial autocorrelation of an AR(p) process is zero at lags greater than p. [5] [8] If an AR model is determined to be appropriate, then the sample partial autocorrelation plot is examined to help identify the ...

  9. Dickey–Fuller test - Wikipedia

    en.wikipedia.org/wiki/Dickey–Fuller_test

    In statistics, the Dickey–Fuller test tests the null hypothesis that a unit root is present in an autoregressive (AR) time series model. The alternative hypothesis is different depending on which version of the test is used, but is usually stationarity or trend-stationarity .