multiple time series cross correlation
- From: hberig <hberig@xxxxxxxxx>
- Date: Fri, 25 Apr 2008 10:07:22 -0700 (PDT)
Hi,
I've different time series, suppose TS1, TS2, TS3, TS4. And I try to
combine TS2, TS3 and TS4 to explain TS1 in the "best possible way".
When I have two time series, for example TS1 and TS2, I can compute
crosscorrelation CCF(TS1, TS2) and take for example the lag L where
CCF is maximum (or other minimum or with maximum module), then
consider for example an increment in TS2 at (T-L) explains an
increment in TS1 in T.
I'm trying to get L1, L2 and L3 lags such that CCF(TS, LAG(TS2, L1) +
LAG(TS2, L2) + LAG(TS3, L3)) is maximum. Is it right? is something
like a combinatorial optimization problem? (TSs are with discrete
domain).
In a principle I think to get Lj such that CCF(TS,LAG(TSj,Lj) is
maximum and then use the Lj's lags. But, may be not the same solution,
or not?
Any help or references (books, text and web pages) about this problem
would be appreciated!
Thanks in advance!
.
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