From: Dennis Shea <shea_at_nyahnyahspammersnyahnyah>

Date: Thu Jun 06 2013 - 13:45:45 MDT

Date: Thu Jun 06 2013 - 13:45:45 MDT

I am not familiar with Weatherhead et al. (1998)

-- Please read the Description section of esccr. This explains how you can get values greater than (+,-) 1 http://www.ncl.ucar.edu/Document/Functions/Built-in/esacr.shtml --- In short, 'qVar' is computed once using the entire series. It uses all 't' values. Hence, it is a constant. c(k) = SUM [(q(t)-qAve)*(q(t+k)-qAve)}]/qVar Technically, at lag 'k' you have N-k values being used. Then, you should calculate the standard deviation using only the N-k values. This would result values always between -1 and +1. However, using the standard deviation of the entire series results in estimates that are asymptotically unbiased and consistent. This is the pat chosen by NCL. On 6/2/13 6:29 PM, Xin Xi wrote: > Hello, > > I am using the method of Weatherhead et al. (1998) to test the significance > of linear trends.I am in the step of computing the auto correlation > coefficient at lag 1 of a 3D time series (lat x lon x time), which is the > noise from detrending a dataset of same dimension. I used the esacr > function and got values larger than 1, while the paper suggested the > autocorrelation coeff should be in the [-1,+1] range. However the formula > used in esacr seems to be right. Can anyone explain why? if you are > familiar with the Weatherhead 1998 paper, is esacr the right function to > use in this case? > > Thanks, > > Xin > > > > _______________________________________________ > ncl-talk mailing list > List instructions, subscriber options, unsubscribe: > http://mailman.ucar.edu/mailman/listinfo/ncl-talk > _______________________________________________ ncl-talk mailing list List instructions, subscriber options, unsubscribe: http://mailman.ucar.edu/mailman/listinfo/ncl-talkReceived on Thu Jun 6 13:45:44 2013

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