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:: Auto Correlation Function ::

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Server date: March 11, 2010, 10:08 am

Auto Correlation Function (ACF) of timeseries Airline.ds by timelag (k)
Degree of non-seasonal differencingd0
Degree of seasonal differencingD0
Box-Cox transformation parameterL1
Standard Error of ACF 0.083333

Time lagAcf(k)T-StatSig.
10.94804711.376568***
20.87557510.506898***
30.8066819.680174***
40.7526259.031505***
50.713778.56524***
60.6817348.180803***
70.6629047.954853***
80.655617.867326***
90.6709488.05138***
100.702728.432639***
110.743248.918882***
120.7603959.124741***
130.7126618.55193***
140.6463427.756107***
150.5859237.031081***
160.5379556.455462***
170.4997485.99697***
180.4687345.624808***
190.4498715.398448***
200.4416295.299546***
210.4572245.486685***
220.4824825.789784***
230.5171276.205524***
240.532196.386278***
250.4939765.927708***
260.4377215.252656***
270.3876034.651235***
280.3480254.1763***
290.3149843.779807***
300.2884973.461962***
310.2708023.249622***
320.264293.171481***
330.2767993.321592***
340.2985213.582258***
350.3255873.907045***
360.3370244.044283***
370.3033353.640018***
computations based on Sample Auto Correlation Formula


Warnings and Comments based on Artificial Intelligence
AI Engine: non-seasonal differencing (d = 1) might be needed to induce stationarity.
Warning: more than 1% of all ACF coefficients are significantly different from zero at the 1% level.


Auto Correlation Function of time series.

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From this analysis it can be concluded that the time series under investigation should be differenced to induce stationarity.
List of last 4 computationsDelete history
Server DateModuleCommand
Thu, 11 Mar 2010 10:08:14 -0700Auto Correlation FunctionPrint | Word | Excel | Blog this | Delete
Thu, 11 Mar 2010 10:08:10 -0700Spearman Rank CorrelationPrint | Word | Excel | Blog this | Delete
Thu, 11 Mar 2010 10:08:02 -0700Simple RegressionPrint | Word | Excel | Blog this | Delete
Thu, 11 Mar 2010 10:07:28 -0700Start of session-
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