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Feb 5 |
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Testing for stationarity in large sample sizes I guess 35400 for one sample part is not too small. Ryogi, do you know any reference where my problem is described in detail? Because I look already for one or two weeks and needed for my thesis...Thanks already for your help. |
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Feb 5 |
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Testing for stationarity in large sample sizes So, if I understand Ryogi correctly if the data is splitted in smaller parts, in general the test will reject the hyphothesis right? But in my case, just the opposite is the case. I have read in Forums, that Hyphothesis test are sensitve to small variations from the process and in large data sets they tend to reject the hypothesis. So I tested the following in R: " x<-rnorm(714000,mean=100,sd=9);kpss.test(x) KPSS Test for Level Stationarity data: x KPSS Level = 0.5604, Truncation lag parameter = 194, p-value = 0.02807 " as we can see, the kpss rejects the data to be stationarity. But if I spli |
