similar to: need help please (HoltWinters function)

Hi. I have to forecast a time series of a Internet network traffic bitrate. The data are in file http://www.forumaltavilla.it/joomla/datitesi/dati.datand the sampling time is every 0.05 seconds. Now, i want to use HoltWinters forecasting. This is my script. dt=1.58443823e-9 #0.05 seconds in years dati.ts=ts(scan("dati.dat"),start=0,deltat=dt) model=HoltWinters(dati.ts)

Hi R-users, I have a question relating to the HoltWinters() function. I am trying to forecast a series using the Holt Winters methodology but I am getting some unusual results. I had previously been using R for Windows version 2.7.2 and have just started using R 2.9.1. While using version 2.7.2 I was getting reasonable results however upon changing versions I found I started to see unusual

i am new to time series,whatever i know up till now,from that i have uploaded time series file & what to build arma model,but for that i want p & q values(orders) tell me how to calculate best p & q values to find best AIC values for model i am doing but giving error >bhavar<-read.table(file.choose()) #taking time series file > decompose(bhavar$V1) Error in

Dear helpers I'm having a problem with function HoltWinters from package ts. I have a time series that I want to fit an Holt-Winters model and make predictions for the next values. I've already built an object of class ts to serve as input to HoltWinters. But then I get an error; I've used HoltWinters a lot of times and this never hapened > data.HW<-HoltWinters(data.ts) Error

Hi everyone, I'm using the HoltWinters() function to do a time series analysis. The function only returns the back fitted values ($fitted) after the first year of data, which is my case, is a little more than half. However, when I use the plot() function, it plots the back fit for almost the entire data set. Any ideas on how to extract the fitted values going all the way back to the start

Hey All, First time on these forums. Thanks in advance. Soooo... I have a process that was functioning well before the 2.14 update. Now the HoltWinters function is throwing an error whereby I get the following: Error in HoltWinters(sales.ts) : optimization failure I've been looking around to determine why this happens (see if I can test the data beforehand) but I haven't come

Full_Name: John Bodley Version: 2.5.1 (2007-06-27) OS: Windows XP Submission from: (NULL) (12.144.182.66) I was fitting a number of time series in R using the stats::HoltWinters method to define a single exponential smoothing model, i.e., beta = gamma = 0. I came across an example where the fitted value of alpha was not defined in the [0, 1] interval which seems to violate the lower and upper

Dear list members I want to analyze separately the months of a time series. In other words, I want to plot and fit models for each month separately. Taking the example of http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/src/timeseries.html births <- scan("http://robjhyndman.com/tsdldata/data/nybirths.dat") birthstimeseries <- ts(births, frequency=12,

i have data in one file below like & (i have such type of file =200,each file have below type of data) >t -0.15264004 0.056076439 -0.07276116 -0.00917326 -0.02069089 -0.00416232 -0.07225855 -0.02654577 -0.06131410 -0.09380202 0.057414014 -0.05239976 0.014397612 0.016145161 -0.00670587 0.018696335 0.036943654 -0.02450233 0.031161705 0.006513503 -0.02892329 -0.00831519 -0.00877744

Hello, I would like to look at the compiled C code behind HoltWinters from the stats package. Is that possible? If so where do I find it? thanks, Spencer [[alternative HTML version deleted]]

I want to forecaste the call number everyday for a call-center. Now I have removed the influence of the fluctuation with some method, so only thing left is to analyze the trend of the call number every day. I have thought of two ways: regression and HoltWinters smooth. But when I use regression, I find some day's call number will bcome negative, which is obviously unreasonabe. If I use

I am running R version 2.14.1 with up-to-date packages. When running the HoltWinters function as in HoltWinters(logjj,gamma=FALSE,beta = TRUE) i get back Smoothing parameters: alpha: 0.1692882 beta : TRUE gamma: FALSE In the old days (several weeks ago) i used to get back the actual beta value used as the documentation states. Is this a reporting change? How can I get the value of

Hello all, I am looking for some help in understanding how to change the way R optimizes the smoothing constant selection process for the HoltWinters function. I'm a SAS veteran but very new to R and still learning my way around. Here is some sample data and the current HoltWinters code I'm using: rawdata <- c(294, 316, 427, 487, 441, 395, 473, 423, 389, 422, 458, 411, 433, 454,

Hi R-help, I'd like to extract the seasonal component of a short timeseries, and was hoping to use stats::decompose. I don't want to decompose the 'trend' component so I thought I should call decompose(x,filter=0). I think I've either misunderstood the filter argument or come upon a bug/feature in decompose. # EXAMPLE

Hello everyone! I´ve started using R last week and I´m having really persistent problems trying to make predictions using the HoltWinters function. I´m sending my script and the errors I´m getting. My data is: Jan Feb Mar Apr May Jun Jul Ago Sep Oct Nov Dec 2004 118 143 169 158 143 135 135 140 135 125.0000 120.0000 120.0000 2005 143 158 180 180 150 150 153 148 150 145.0000

I get John's value (48.8789) in 2.7.0 and R-devel (both on Ubuntu). Really seems to be a numeric issue: > HoltWinters(x, beta = 0, gamma = 0)$alpha alpha 48.87989 > HoltWinters(x * 1.0000000001, beta = 0, gamma = 0)$alpha alpha 0.6881547 > HoltWinters(x * 1.00000000001, beta = 0, gamma = 0)$alpha alpha 48.87989 Providing starting values seems to help, but not

An update on this: I just patched HoltWinters() to use optimize() in the univariate case, and it now computes the correct value. David John Bodley wrote: > Hi, > > Thanks for the quick response. I upgraded by version of R on Windows to the > latest (2.7.0) and re-ran the analysis and get the same result of 48.87989. > > The original time series was a non-regular zoo()

It doesn't do it on my system (I get a value of about 0.688 in R 2.7.0 patched on Linux), and 2.5.1 is not current. Does a better starting value help? However, HoltWinters is using optim() in a case it is not designed for (one-dimensional optimization): see the note on its help page. I think this could easily be changed, but as HoltWinters is contributed code I am Cc:ing the author for

Is there any way to give a "decent" title after I plot something generated by decompose? For example: # generate something with period 12 x <- rnorm(600) + sin(2 * pi * (1:600) / 12) # transform to a monthy time series y <- ts(x, frequency=12, start=c(1950,1)) # decompose z <- decompose(y) # plot plot(z) Now, the title is the ugly "Decomposition of additive time

Dear All, I was wondering why the forecast for an additive HoltWinters model is given by Yhat[t+h] = a[t] + h * b[t] + s[t + 1 + (h - 1) mod p]. I am a student and new to time series analysis and forecasting. That said, I considered t = 13 and h = 1: Yhat[13+1] = a[13] + b[13] + s[13 + 1] It seems odd that to predict Yhat[14], you would need a s[14] which in turn depends on Y[14], given that