My data is sampled once per minute. There are invalid samples, leaving a lot of holes in the samples, successful sample is around 80% of all minutes in a day. and during the last 4 months sampling, one month's data was stored on a harddisk that failed, leaving a month's gap in between.
So am I working with regularly spaced time series or not? Should I padd all missing data with NAs, and start with ts(), and followed by forecast package (which seems to have all the functions I need in the begining) or should I start with a library with irregular time series in mind? Also, ts() manual didn't say how to create time-series with one minute as daltat. Its seems to assume time-series is about dates. So the data I have with me, is it really time series at all? Newbie question indeed. Thanks. ______________________________________________ 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.
