Orange: Granger Causality - Revision history

Onnowpurbo: /* Input */

2020-04-06T23:34:40Z

Input

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	Widget Granger Causality melakukan beberapa test statistik untuk mengetahui bahwa series ini menyebabkan series lain sehingga kita dapat menggunakan series sebelumnya untuk mem-forcast series yang kemudian.		Widget Granger Causality melakukan beberapa test statistik untuk mengetahui bahwa series ini menyebabkan series lain sehingga kita dapat menggunakan series sebelumnya untuk mem-forcast series yang kemudian.

	[[File:Granger-causality-stamped.png\|center\|~~200px~~\|thumb]]		[[File:Granger-causality-stamped.png\|center\|400px\|thumb]]

	* Desired level of confidence.		* Desired level of confidence.

Onnowpurbo at 23:33, 6 April 2020

2020-04-06T23:33:56Z

← Older revision		Revision as of 23:33, 6 April 2020
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	* The effect (consequent) series.		* The effect (consequent) series.

	Time series yang Granger-cause series ~~yang kita tertarik~~ adalah kandidat yang baik untuk dimasukan dalam VAR model yang sama. Akan tetapi kita harus berhati-hati, meskipun sebuah series di katakan Granger-cause yang lain, ini tidak berarti pasti ada hubungan ~~casual di~~ antara series tersebut. Oleh karenanya, berhati-hati lah.		Time series yang Granger-cause series adalah kandidat yang baik untuk dimasukan dalam VAR model yang sama. Akan tetapi kita harus berhati-hati, meskipun sebuah series di katakan Granger-cause yang lain, ini tidak berarti pasti ada hubungan antara series tersebut. Oleh karenanya, berhati-hati lah.

	==Referensi==		==Referensi==

Onnowpurbo at 23:32, 6 April 2020

2020-04-06T23:32:50Z

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	~~Test~~ untuk mencek apakah sebuah time series Granger-causes (yaitu, menjadi indikator dari) time series yang lain.		Widget Granger Causality melakukan test untuk mencek apakah sebuah time series Granger-causes (yaitu, menjadi indikator dari) time series yang lain.

	==Input==		==Input==
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	Time series: Time series as output by As Timeseries widget.		Time series: Time series as output by As Timeseries widget.

	Widget melakukan beberapa test statistik untuk mengetahui bahwa series ini menyebabkan series lain sehingga kita dapat menggunakan series sebelumnya untuk mem-forcast series yang kemudian.		Widget Granger Causality melakukan beberapa test statistik untuk mengetahui bahwa series ini menyebabkan series lain sehingga kita dapat menggunakan series sebelumnya untuk mem-forcast series yang kemudian.

	[[File:Granger-causality-stamped.png\|center\|200px\|thumb]]		[[File:Granger-causality-stamped.png\|center\|200px\|thumb]]

Onnowpurbo at 11:19, 11 March 2020

2020-03-11T11:19:39Z

← Older revision		Revision as of 11:19, 11 March 2020
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	Time series: Time series as output by As Timeseries widget.		Time series: Time series as output by As Timeseries widget.

	~~Widgets performs a~~ series ~~of statistical tests to determine the~~ series ~~that cause other~~ series ~~so we can use the former to forecast the latter~~.		Widget melakukan beberapa test statistik untuk mengetahui bahwa series ini menyebabkan series lain sehingga kita dapat menggunakan series sebelumnya untuk mem-forcast series yang kemudian.

	[[File:Granger-causality-stamped.png\|center\|200px\|thumb]]		[[File:Granger-causality-stamped.png\|center\|200px\|thumb]]
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	* The effect (consequent) series.		* The effect (consequent) series.

	~~The time~~ series ~~that~~ Granger-cause ~~the~~ series ~~you are interested in are good candidates to have in the same~~ VAR model. ~~But careful~~, ~~even if one~~ series ~~is said to~~ Granger-cause ~~another~~, ~~this doesn’t mean there really exists a causal relationship~~. ~~Mind your conclusions~~.		Time series yang Granger-cause series yang kita tertarik adalah kandidat yang baik untuk dimasukan dalam VAR model yang sama. Akan tetapi kita harus berhati-hati, meskipun sebuah series di katakan Granger-cause yang lain, ini tidak berarti pasti ada hubungan casual di antara series tersebut. Oleh karenanya, berhati-hati lah.


	==Referensi==		==Referensi==

Onnowpurbo at 08:44, 27 February 2020

2020-02-27T08:44:43Z

← Older revision		Revision as of 08:44, 27 February 2020
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	Test ~~if one~~ time series Granger-causes (~~i.e. can be an indicator of~~) ~~another~~ time series.		Test untuk mencek apakah sebuah time series Granger-causes (yaitu, menjadi indikator dari) time series yang lain.

	==Input==		==Input==
Line 8:		Line 8:
	Time series: Time series as output by As Timeseries widget.		Time series: Time series as output by As Timeseries widget.

	~~This widgets~~ performs a series of statistical tests to determine the series that cause other series so we can use the former to forecast the latter.		Widgets performs a series of statistical tests to determine the series that cause other series so we can use the former to forecast the latter.

	[[File:Granger-causality-stamped.png\|center\|200px\|thumb]]		[[File:Granger-causality-stamped.png\|center\|200px\|thumb]]

Onnowpurbo at 23:25, 29 January 2020

2020-01-29T23:25:00Z

← Older revision		Revision as of 23:25, 29 January 2020
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	Test if one time series Granger-causes (i.e. can be an indicator of) another time series.		Test if one time series Granger-causes (i.e. can be an indicator of) another time series.

	~~Inputs~~		==Input==

	Time series: Time series as output by As Timeseries widget.		Time series: Time series as output by As Timeseries widget.

	This widgets performs a series of statistical tests to determine the series that cause other series so we can use the former to forecast the latter.		This widgets performs a series of statistical tests to determine the series that cause other series so we can use the former to forecast the latter.
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	[[File:Granger-causality-stamped.png\|center\|200px\|thumb]]		[[File:Granger-causality-stamped.png\|center\|200px\|thumb]]

	Desired level of confidence.		* Desired level of confidence.
	Maximum lag to test to.		* Maximum lag to test to.
	Runs the test.		* Runs the test.
	Denotes the minimum lag at which one series can be said to cause another. In the first line of the example above, if we have the monthly unemployment rate time series for Austria, we can say something about unemployment rate in Hungary 10 months ahead.		* Denotes the minimum lag at which one series can be said to cause another. In the first line of the example above, if we have the monthly unemployment rate time series for Austria, we can say something about unemployment rate in Hungary 10 months ahead.
	The causing (antecedent) series.		* The causing (antecedent) series.
	The effect (consequent) series.		* The effect (consequent) series.

	The time series that Granger-cause the series you are interested in are good candidates to have in the same VAR model. But careful, even if one series is said to Granger-cause another, this doesn’t mean there really exists a causal relationship. Mind your conclusions.		The time series that Granger-cause the series you are interested in are good candidates to have in the same VAR model. But careful, even if one series is said to Granger-cause another, this doesn’t mean there really exists a causal relationship. Mind your conclusions.

Onnowpurbo at 00:30, 26 January 2020

2020-01-26T00:30:32Z

← Older revision		Revision as of 00:30, 26 January 2020
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	This widgets performs a series of statistical tests to determine the series that cause other series so we can use the former to forecast the latter.		This widgets performs a series of statistical tests to determine the series that cause other series so we can use the former to forecast the latter.

			[[File:Granger-causality-stamped.png\|center\|200px\|thumb]]

	Desired level of confidence.		Desired level of confidence.

Onnowpurbo: Created page with "Sumber: https://orange.biolab.si/widget-catalog/time-series/granger_causality/ Test if one time series Granger-causes (i.e. can be an indicator of) another time series. Inp..."

2020-01-20T03:15:45Z

Created page with "Sumber: https://orange.biolab.si/widget-catalog/time-series/granger_causality/ Test if one time series Granger-causes (i.e. can be an indicator of) another time series. Inp..."

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

Test if one time series Granger-causes (i.e. can be an indicator of) another time series.

Inputs

Time series: Time series as output by As Timeseries widget.

This widgets performs a series of statistical tests to determine the series that cause other series so we can use the former to forecast the latter.

Desired level of confidence.
Maximum lag to test to.
Runs the test.
Denotes the minimum lag at which one series can be said to cause another. In the first line of the example above, if we have the monthly unemployment rate time series for Austria, we can say something about unemployment rate in Hungary 10 months ahead.
The causing (antecedent) series.
The effect (consequent) series.

The time series that Granger-cause the series you are interested in are good candidates to have in the same VAR model. But careful, even if one series is said to Granger-cause another, this doesn’t mean there really exists a causal relationship. Mind your conclusions.

==Referensi==

* https://orange.biolab.si/widget-catalog/time-series/granger_causality/

==Pranala Menarik==

* [[Orange]]