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Refers to the AutoRegressive Integrated Moving Average model used in time series modeling both for data description and for forecasting. This model generalizes the ARMA model by including a term for differencing, which is useful for removing trends and handling some types of non-stationarity.

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time-series analysis Vs statistical signal processing

For one ARIMA is a parametric method (assumption of a fixed distribution) modeling a stationary time series based on static ARMA terms while with wavelets you model a wavelet function by selecting a list … In ARIMA you aproximate the signal components by selecting ARMA terms from acf and pacf while for wavelets you aproximate the signal by selecting a mother wavelet, filter length and number of vanishing …
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