ARIMA

ARIMA

ARIMA is located under Forecasting > Modeling > ARIMA. Use the drag-and-drop method (or double-click on the node) to use the algorithm in the canvas. Click the algorithm to view and select different properties for analysis.



Properties of ARIMA

The properties of ARIMA are shown in the figure below.


The following table shows the properties of ARIMA.

Field

Description

Remark


It helps execute the node

-


It helps to explore the successful node.

-


It displays the following options in the list view.

  • Run till node
  • Run from node
  • Publish as a model
  • Publish code

-

Task Name

It is the name of the task selected on the workbook canvas.

You can click the text field to edit or modify the task name as required.

Time ID Variable

It allows you to select the interval type variable for which we need to process the dependent or target variable's values.

  • Only one data field can be selected.
  • If selected, only an interval type variable should be selected.
  • Variables with numerical value are not available.

Target Variable

It allows you to select the experimental or predictor variable(s).

  • Only one data field can be selected.
  • Variables with only numerical values are available.

Group By

It allows you to select the variable for which you want to group the data.

  • Multiple data field can be selected.
  • Only categorical type variables are available.

ADVANCED

Number of Periods for Forecasting

It allows you to select the values for the forecast

  • Only positive integers can be selected

Interval

It allows to select the interval for the accumulation of data in the accumulation test.

Available options are –

  • Day
  • Week
  • Month
  • Quarter
  • Year
    The default value is Month.

p

It allows to select the Autoregression order

Preferred values are from 0 to 9

d

It allows to select order of differencing

Preferred values are from 0 to 2

q

It allows to select Moving averages order

Preferred values are from 0 to 9

Trend Offset

It is the offset at which time trend values start.

The values must be integers

Trend

It allows selecting parameter for controlling the deterministic trend.

Available options are

  • None
  • n
  • c
  • t
  • ct

Enforce Stationarity

It allows you to select the autoregressive parameters to correspond to a stationarity process.

Available options are

  • True
  • False

Enforce invertibility

It allows you to select the moving average parameters to correspond to an invertible process.

Available options are

  • True
  • False

Example of ARIMA

Consider the Air Passengers dataset. The snippet of input data is shown below.



We apply the Train Test Split to the input data and then apply the ARIMA to the Train Test Split node.



We select the TravelDate as the Time Id Variable and Passengers Target variable.



Further, the result page displays,

  • Forecasting chart with predicted value.
  • Trained Model Parameters
  • Accuracy Parameters



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