HI,
I guess you can check library(forecast).
You could also use ?stl(), though not sure whether this will help you in this
case.
For e.g.
set.seed(5)
quantity<-sample(c(120:220,NA),699,replace=TRUE)
Date=seq(as.Date("2011-01-01"),len=699,by="1 day")
dat3<-data.frame(Date=Date,quantity=quantity)
library(zoo)
z <- zooreg(dat3[,2], frequency = 7)
plot(stl(na.approx(z),"per"))
A.K.
----- Original Message -----
From: mekbatub <mekba...@gmail.com>
To: r-help@r-project.org
Cc:
Sent: Saturday, December 1, 2012 8:00 PM
Subject: Re: [R] Daily Time Series, patterns.
Hi Arun, thx for Your reply.
thats interesting, but its not what I mean.
I know that there is some patterns in data, example:
the highest value of the sale is on Monday, and the smallest on Wednesday
and so on, there might be trend also
I am trying to build forecasting model that will include patterns like that,
for example forecast to next 5 days. So i think I can say that is weekly
sesonality, i believe the metod to make correct model is to decompose time
series like there.
http://otexts.com/fppfigs/elecequip_stl.png
<http://otexts.com/fppfigs/elecequip_stl.png>
Do You think I am right? In any case, I have big problem to do this in R.
--
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