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-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Im Auftrag von Cuckovic Paik Gesendet: Freitag, 29. Oktober 2010 05:48 An: r-help@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. -- View this message in context: http://r.789695.n4.nabble.com/Dickey-Fuller-Test-tp3018408p3018408.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ***************************************************************** Confidentiality Note: The information contained in this ...{{dropped:10}} ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
