Orange: Granger Causality - Revision history

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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..."

New page

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]]

@@ Line 10: / Line 10: @@
 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.

@@ Line 19: / Line 19: @@
 * 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==

@@ Line 2: / Line 2: @@
-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==
@@ Line 8: / Line 8: @@
   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]]

@@ Line 8: / Line 8: @@
   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]]
@@ Line 19: / Line 19: @@
 * 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==

@@ Line 2: / Line 2: @@
-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==
@@ Line 8: / Line 8: @@
   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]]

← 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.