View source for Autoregressive Integrated Moving Average (ARIMA) Algorithm

An [[Autoregressive Integrated Moving Average (ARIMA) Algorithm]] is a [[parametric timeseries modeling algorithm|parametric]] [[univariate timeseries modeling algorithm]] with [[non-negative integer]]s (p,d,q) which refer to the [[order of the autoregressive]], [[integrated]], and [[moving average]] [[algorithm parameter]]s
* <B>Context:</B>
** <B>[[Algorithm Parameter|parameter]]s</B>: [[Autoregressive Integrated Moving Average (ARIMA) Algorithm|ARIMA]](''p'',''d'',''q''), where ''p'', ''d'', and ''q'' are [[non-negative integer]]s that refer to the order of the autoregressive, integrated, and moving average parts.
** It can be implemented by an [[ARIMA-based system]] (to solve an [[ARIMA-based task]] that produces an [[trained ARIMA model structure]]).
** …
* <B>Example(s):</B>
** an [[ARMA Model]] (is a specialization?)
** a [[Seasonal ARIMA Algorithm]].
** …
* <B>Counter-Example(s):</B>
** a [[Naive Forecasting Algorithm]], such as a [[moving average model]], or an [[exponential forecasting algorithm]].
** a [[Kalman Filter]].
** a [[Vector Autoregressive Algorithm]].
* <B>See:</B> [[Box-Jenkins Algorithm]], [[Multi-Relational Data Mining]], [[ARCH Model]], [[Timeseries Analysis Method]].

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