Orange: ARIMA Model: Difference between revisions

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Model time series menggunakan model ARMA, ARIMA, atau ARIMAX.
Widget ARIMA Model me-model-kan time series menggunakan model ARMA, ARIMA, atau ARIMAX.


==Input==
==Input==
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  Residuals: The errors the model made at each step.
  Residuals: The errors the model made at each step.


Menggunakan widget ini, kita dapat me-model time series menggunakan model ARIMA.
Menggunakan widget ARIMA Model, kita dapat me-model time series menggunakan model ARIMA.


[[File:Arima-model-stamped.png|center|200px|thumb]]
[[File:Arima-model-stamped.png|center|400px|thumb]]


* Model’s name. By default, the name is derived from the model and its parameters.
* Model’s name. By default, the name is derived from the model and its parameters.
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==Contoh==
==Contoh==


[[File:Arima-model-ex1.png|center|200px|thumb]]
[[File:Arima-model-ex1.png|center|600px|thumb]]





Revision as of 23:55, 6 April 2020

Sumber: https://orange.biolab.si/widget-catalog/time-series/arima/


Widget ARIMA Model me-model-kan time series menggunakan model ARMA, ARIMA, atau ARIMAX.

Input

Time series: Time series as output by As Timeseries widget.
Exogenous data: Time series of additional independent variables that can be used in an ARIMAX model.

Output

Time series model: The ARIMA model fitted to input time series.
Forecast: The forecast time series.
Fitted values: The values that the model was actually fitted to, equals to original values - residuals.
Residuals: The errors the model made at each step.

Menggunakan widget ARIMA Model, kita dapat me-model time series menggunakan model ARIMA.

  • Model’s name. By default, the name is derived from the model and its parameters.
  • ARIMA’s p, d, q parameters.
  • Use exogenous data. Using this option, you need to connect additional series on the Exogenous data input signal.
  • Number of forecast steps the model should output, along with the desired confidence intervals values at each step.

Contoh


See also

VAR Model, Model Evaluation


Referensi

Pranala Menarik