Dear listers,
I am working on a time series but find that for a given non-zero time
lag correlations obtained by ccf and cor are different.
x <- c(0.85472102802704641, 1.6008990694641689, 2.5019632258894835,
2.514654801253164, 3.3359198688206368, 3.5401357138398208,
2.6304117871193538, 3.6694074965420009, 3.9125153101706776,
4.4006592535478566, 3.0208991912866829, 2.959090589344433,
3.8434635568566056, 2.1683644330520457, 2.3060571563512973,
1.4680350663043942, 2.0346918622459054, 2.3674524446877538)
y <- c(2.3085729270534765, 2.0809088217491416, 1.6249456563631131,
1.5133386666933177, 0.66754156827555422, 0.3080839731181978,
0.52653042555599394, 0.89070463020837132, 0.71600791432232669,
0.82152341002975027, 0.22200290782700527, 0.6608410635137173,
0.90715232876618945, 0.45624062770725898, 0.35074487486980244,
1.1681750562971052, 1.6976462236079737, 0.88950230250556417)
cc<-ccf(x,y)
> cc Autocorrelations of series ‘X’, by lag -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1
2 0.098 0.139 0.127 -0.043 -0.049 0.069 -0.237 -0.471 -0.668 -0.595
-0.269 -0.076 3 4 5 6 7 8 9 -0.004 0.123 0.272 0.283 0.401 0.435 0.454
cor(x,y) [1] -0.5948694
So far so good, but when I lag one of the series, I cannot find the same
correlation as with ccf
> cor(x[1:(length(x)-1)],y[2:length(y)]) [1] -0.7903428
... where I expect -0.668 based on ccf
Can anyone explain why ?
Best,
Patrick
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