Hi,
I'm used to the following definition of autocorrelation:
R(\tau) = \frac{<(X_t - \mu)(X_{t+\tau}-\mu)>}{\sigma^2}
However, it looks like acorr is just giving me
R(\tau) = \sum{X_t*X_{t+\tau}}
Just specifying normed=True doesn't get the first formula. Is there some
trivial option that I've missed?
Here's what I did:
It's easy enough to subtract \mu from my timeseries, but when I ask acorr to
normalize things for me, I get the whole timeseries normalized by the value
of R(0):
if normed: c/= np.dot(x,x)
I really do want the formula I gave, which requires each point of the
autocorrelation to be averaged separately. So, I modified my local version
of acorr to say
if normed:
nrm = arange(len(x))
nrm = hstack((nrm,nrm[:-1][::-1]))*std(x)**2
c /= nrm
Thanks,
-michael
--
Michael Lerner, Ph.D.
IRTA Postdoctoral Fellow
Laboratory of Computational Biology NIH/NHLBI
5635 Fishers Lane, Room T909, MSC 9314
Rockville, MD 20852 (UPS/FedEx/Reality)
Bethesda MD 20892-9314 (USPS)
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