Dear All, I am trying to determine the cross correlation between two different time series of data which is collected based on different sampling frequency. i.e (daily data and intraday day).
When I plot this data I can clearly see that there is one series lags another, BUT in terms of quantifying this the ccf function treats each data point as the same time period => false correlation results. Is there a way to aggregate data in a way such that two time series can have the same length for analysis purposes. My data essentially would look like this Daily = Day_1, Day_2, Day_3, ... , Day_n Intraday = Day_(1,1), Day_(1,2),Day(2,1),Day(2,2), ..., Day(n,1),Day(n,2) where Day_(i,j) represents the j-th part of the i-th day. Thanks in advance, Sean -- View this message in context: http://www.nabble.com/Cross-Correlations-for-two-time-series%2C-different---of-observations-tp24042024p24042024.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
