Hi all,
   
  Hope you people do not feel irritated for repeatedly sending mail on Time series.
   
  Here I got another problem on the same, and hope I would get some answer from you.
   
  I have following dataset:
   
  data[,1]
  [1] 4.96 4.95 4.96 4.96 4.97 4.97 4.97 4.97 4.97 4.98 4.98 4.98 4.98 4.98 4.99 4.99 5.00 5.01
 [19] 5.01 5.00 5.01 5.01 5.01 5.01 5.02 5.01 5.02 5.02 5.03 5.03 5.03 5.03 5.03 5.04 5.04 5.04
 [37] 5.04 5.04 5.04 5.05 5.05 5.06 5.06 5.06 5.07 5.07 5.07 5.07 5.08 5.07 5.08 5.08 5.09 5.10
 [55] 5.10 5.09 5.10 5.10 5.10 5.10 5.10 5.10 5.10 5.10 5.11 5.11 5.11 5.11 5.11 5.11 5.11 5.12
 [73] 5.12 5.12 5.12 5.13 5.14 5.14 5.14 5.14 5.14 5.15 5.15 5.15 5.15 5.14 5.15 5.15 5.15 5.16
 [91] 5.16 5.16 5.16 5.16 5.16 5.16 5.16 5.16 5.16 5.16 5.17 5.17 5.17 5.17 5.17 5.18 5.18 5.18
[109] 5.18 5.18 5.19 5.19 5.20 5.20 5.20 5.20 5.20 5.21 5.21 5.21 5.21 5.21 5.21 5.22 5.22 5.23
[127] 5.23 5.23 5.23 5.24 5.24 5.24 5.25 5.24 5.24 5.25 5.26 5.26 5.26 5.26 5.26 5.26 5.26 5.27
[145] 5.27 5.26 5.27 5.27 5.28 5.29 5.29 5.29 5.29 5.30 5.30 5.30 5.31 5.31 5.31 5.32 5.32 5.33
[163] 5.33

   
  Now I want to conduct a test for stationarity using ADF test :
   
  > adf.test((data[,1]), "stationary",  0)
          Augmented Dickey-Fuller Test
  data:  (data[, 1]) 
Dickey-Fuller = -3.7351, Lag order = 0, p-value = 0.02394
alternative hypothesis: stationary 

  But surprisingly it leads towards rejestion of NULL [p-value is less than 0.05], i.e. indicates a possible stationary series. However ploting a graph of actual data set it doesn't seem so.
   
  Am I making any mistakes ? Can anyone give me any suggestion?
   
  Regards,
  Megh

       
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