similar to: HoltWinters Forecasting

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

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

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

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

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)

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]]

every time i try to run HoltWinters i get this error message: > HoltWinters(z, seasonal="additive") Error in decompose(ts(x[1:wind], start = start(x), frequency = f), seasonal) : time series has no or less than 3 periods what's going on? somebody please help me. -- View this message in context:

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,

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()

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

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

Hi, I am trying to fit the HoltWinters exponential smoothing on a monthly time series data in R. My questions are: 1. I know that the level, trend and seasonality are updated over time. So are the output coefficients a, b and s1-s12 for a specific time t (a,b and s12 for last observataion for example) ? 2. I am trying to work out the fitted values but I could not figure out the h value used in

Hello, I have noticed a potentially confusing implementation in the HoltWinters function regarding the seasonal parameter mapping between R and C code: https://github.com/wch/r-source/blob/4a1ed749271c52e60a85e794e6f34b0831efb1ae/src/library/stats/R/HoltWinters.R#L98 The C code interprets a seasonal value of 1 as additive and 0 as multiplicative. The R seasonal can be "additive" or

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

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,

Need your expertise for the theoretical approach to deduce the p-values for the level, trend and seasonality parameters. I wonder if there's source code available. Thanks group. Kel

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

hi i try to use arima and holtwinter to predict drought from 1895-2006 but i cannot read whole period of time and i try to do the exponent fitting, but it comes out as the coordinate x-y error i send the source code and data to take a look if anyone can help me, i am really new in R thank u so much jam

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