Hi Arun, thanks again, I think we are close. The way You gave me looks good, but I sill have one problem, look at this:
Lets say, we have data like this: >head(dat3) Date quantity 2012-03-05 65.16 2012-03-06 70.67 2012-03-08 63.66 2012-03-09 70.05 2012-03-12 61.59 2012-03-13 58.98 Then we have: >z <- zooreg(dat3[,2], frequency = 5) >z 1(1) 1(2) 1(3) 1(4) 1(5) 2(1) 65.16 70.67 63.66 70.05 61.59 58.98 This is for dates: 1(1) 1(2) 1(3) 1(4) 1(5) 2(1) 2012-03-05 2012-03-06 2012-03-08 2012-03-09 2012-03-12 2012-03-13 Since there was no releases in 2012-03-07 (warehouse was closed) We should have: 1(1) 1(2) *1(4) 1(5) 1(1) 2(2) * 65.16 70.67 63.66 70.05 61.59 58.98 So I can’t in that case use “frequency=5”. I am trying to figure out how to assign correctly number of the week day to quantity. I am wondering if my way of thinking is correct, maybe I should fill out those missing values like You suggest me last time, but the problem is there are not missing values really, for ex. if the warehouse was closed, there was not supposed to be releases that day so there is nothing to fill out really. I am wondering is it at all possible to do this in R like I am trying to do – without data continuity. What You think about that? -- View this message in context: http://r.789695.n4.nabble.com/Daily-Time-Series-patterns-tp4651569p4651836.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.