[R] Dickey Fuller Test

[Pfaff, Bernhard Dr.]

Dear Cuckovic,

although you got already an answer to your post that relates a little bit more on the time series characteristics of your data in question; I will take up on your initial question. Basically, you got trapped by the word 'time series' in the documentation for adf.test(). What is meant, is an object of informal class ts, hence:

YYY <- as.ts(Y)
adf.test(Y)
adf.test(YYY)

does yield the same result. Now, what's happening if an object of formal class timeSeries is inserted? Well, have a look at adf.test directly: adf.test

Here, you will see that the series becomes differenced, but this operation is applied differently for numeric/ts objects viz. timeSeries objects; check:

showMethods(diff)

and/or

diff(Y)
diff(YY)
diff(YYY)

Now, to rectify your results, use:

adf.test(series(YY)) instead. Here, the data part of your timeSeries object is extracted only and hence the same method for diff() is used as in the case of numeric/ts objects.

Best,
Bernhard

-----Ursprüngliche Nachricht-----
Von: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] Im Auftrag von Cuckovic Paik
Gesendet: Freitag, 29. Oktober 2010 05:48
An: r-help at r-project.org
Betreff: [R] Dickey Fuller Test


Dear Users, please help with the following DF test:
=====
library(tseries)
library(timeSeries)

Y=c(3519,3803,4332,4251,4661,4811,4448,4451,4343,4067,4001,3934,3652,3768
,4082,4101,4628,4898,4476,4728,4458,4004,4095,4056,3641,3966,4417,4367
,4821,5190,4638,4904,4528,4383,4339,4327,3856,4072,4563,4561,4984,5316
,4843,5383,4889,4681,4466,4463,4217,4322,4779,4988,5383,5591,5322,5404
,5106,4871,4977,4706,4193,4460,4956,5022,5408,5565,5360,5490,5286,5257
,5002,4897,4577,4764,5052,5251,5558,5931,5476,5603,5425,5177,4792,4776
,4450,4659,5043,5233,5423,5814,5339,5474,5278,5184,4975,4751,4600,4718
,5218,5336,5665,5900,5330,5626,5512,5293,5143,4842,4627,4981,5321,5290
,6002,5811,5671,6102,5482,5429,5356,5167,4608,4889,5352,5441,5970,5750
,5670,5860,5449,5401,5240,5229,4770,5006,5518,5576,6160,6121,5900,5994
,5841,5832,5505,5573,5331,5355,6057,6055,6771,6669,6375,6666,6383,6118
,5927,5750,5122,5398,5817,6163,6763,6835,6678,6821,6421,6338,6265,6291
,5540,5822,6318,6268,7270,7096,6505,7039,6440,6446,6717,6320)

YY=as.timeSeries(Y)

adf.test(Y)
adf.test(YY)
========  Output ====
> adf.test(Y)

        Augmented Dickey-Fuller Test

data:  Y
Dickey-Fuller = -6.1661, Lag order = 5, p-value = 0.01 alternative hypothesis: stationary 

Warning message:
In adf.test(Y) : p-value smaller than printed p-value
> adf.test(YY)

        Augmented Dickey-Fuller Test

data:  YY
Dickey-Fuller = 12.4944, Lag order = 5, p-value = 0.99 alternative hypothesis: stationary 

Warning message:
In adf.test(YY) : p-value greater than printed p-value
> 
==========================================
Question: Why the two results are different?

The help file says that the input series is either a numeric vector or a time series object. But the results are completely opposite if the different types of arguments are used. Thanks in advance.







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