Perhaps looking at your data will suggest an appropriate number, viz.
plot(data,type="b",xlim=c(0,20),ylim=c(0,50))
par(new=T)
ind<-1:19 # in this case where the data length is 19
data.ind<-data.frame(ind,data)
data.lo<-loess(data~ind,data.ind)
data.pre<-predict(data.lo,data.frame(ind = seq(1,19,1)))
plot(data.pre,pch=3,col=2,xlim=c(0,20),ylim=c(0,50))
If you now plot the difference between the data and the loess prediction,
data.ind<-cbind(data.ind,data.pre)
data.diff<-with(data.ind,data-data.pre)
data.ind<-cbind(data.ind,data.diff)
with(data.ind,plot(ind,data.diff,type="b"))
abline(h=0)
there is also a pretty strong two week signal--is that of any interest?
Now you should be able to decide how to proceed.
Clint
Clint Bowman INTERNET: cl...@ecy.wa.gov
Air Quality Modeler INTERNET: cl...@math.utah.edu
Department of Ecology VOICE: (360) 407-6815
PO Box 47600 FAX: (360) 407-7534
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On Fri, 4 Oct 2013, Daniel Hickman wrote:
Bill,
Thanks for replying.
The data is weekly time series data. Assume there is 52 weeks in the year. Of
the 52 weeks, I typically only have data for weeks 8 through 40.
4-Apr-10, 8, 27.2
11-Apr-10, 9, 32.3
18-Apr-10, 10, 31.7
DataXYZ, 40, 13.4
data <-
c(0,24.57,29.93,24.19,12.25,48.07,36.68,24.78,48.69,30.39,48.17,36.51,36.43,36.52,48.75,24.17,37.07,0,18.89)
ts <- ts(data= data, start = 8, end = 40, frequency = ????)
There is a weekly seasonality effect. What should I set my frequency value to?
Thanks,
Dan Hickman
From: William Dunlap
Sent: ???Thursday???, ???October??? ???3???, ???2013 ???3???:???57??? ???PM
To: David Winsemius, Daniel Hickman
Cc: r-help@r-project.org
ts <- ts(data$QtyPerWeek, frequency=52)
HoltWinters(ts,0.46924,0.05,0.2)
This results in the following error. "Error in decompose(ts(x[1L:wind], start =
start(x),
frequency = f), seasonal) : time series has no or less than 2 periods"
Since you have set the frequency of the time series to 52, you need
to have 104 observations to get the initial estimate of the seasonal
pattern. How many observations are in 'ts'? If you don't have enough
you can omit the seaonal component (HoltWinters(gamma=FALSE,...)),
change start.periods from the default 2 to 1, or supply a 52-long vector
of the initial seasonal pattern as the s.start argument.
If you do have more than 104 observations then you will have to tell
us more about the data.
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
-----Original Message-----
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf
Of David Winsemius
Sent: Thursday, October 03, 2013 12:39 PM
To: Daniel Hickman
Cc: r-help@r-project.org
Subject: Re: [R] time series has no or less than 2 periods
On Oct 3, 2013, at 8:32 AM, Daniel Hickman wrote:
Hello,
I have been tasked with taking an excel file that my colleague had implemented
Triple
Exponential Smoothing and recreate using R.
The following image shows the before and after of smoothing out a fixed
interval time
series data using Triple Exponential Smoothing inside of Excel.
enter image description here
The image file formats that I know are acceptable are .ps, .pdf or .png. Not
sure about
jpeg.
I am trying to perform the same triple exponential smoothing in R. I created a
csv file
with the before smoothing data. The csv file is attached and can also be found
here.
Need to send with .txt extension.
I found the HoltWinters method but I keep getting an error when I try to apply
HoltWinters against the csv.
setwd("C:/temp")
data <- read.table("TripleExpSmoothingXLS.csv", header=TRUE, sep=",")
ts <- ts(data$QtyPerWeek, frequency=52)
HoltWinters(ts,0.46924,0.05,0.2)
This results in the following error. "Error in decompose(ts(x[1L:wind], start =
start(x),
frequency = f), seasonal) : time series has no or less than 2 periods"
Perhaps a data entry problem. We would need to see either the file or output of
str(data).
In case it helps, excel file with the triple exponential smoothing formulas
and original
data can be found here.
Again.... there is no here here.
Any advice?
Thanks, Dan______________________________________________
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David Winsemius
Alameda, CA, USA
______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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and provide commented, minimal, self-contained, reproducible code.
