similar to: Query regarding auto arima

I am using auto.arima() for forecasting.When I am using any in built data such as "AirPassangers" it is capturing seasonality. But, If I am entering data in any other format(in vector form or from an excel sheet) it is not detecting seasonality. Is there any specific format in which it detects seasonality or I am doing some thing wrong? Does data have to be entered in a specific

How we can call auto.arima in R. Is there any cran package we need to install for this function? -- Siddharth Arun, 4th Year Undergraduate student Industrial Engineering and Management, IIT Kharagpur [[alternative HTML version deleted]]

I am not able to run Dickey-Fuller test. adf.test() function is not working. It is showing 'Error: could not find function "adf.test" Can any tell how to call "time series" library? -- Siddharth Arun, 4th Year Undergraduate student Industrial Engineering and Management, IIT Kharagpur [[alternative HTML version deleted]]

I am new in R. Can anyone tell : 1. how we can write our own functions in R ? 2. how we can save those functions and recall to use them? 3. what extensions are used for saving a file? -- Siddharth Arun, 4th Year Undergraduate student Industrial Engineering and Management, IIT Kharagpur [[alternative HTML version deleted]]

Greetings, I am trying to model a time series using arima(). For getting the model order components(p, d, q and P,D,Q) I am using procedure discussed in [1] in section 3.2 . It is most likely hit and trial method based on lower AIC value. I want to know what is the correct way to find model order components or the method described in [1] is the appropriate one. thanks in advance. -- [1]Automatic

Hello, I'm an R newbie. I've tried to search, but my search skills don't seem up to finding what I need. (Maybe I don't know the correct terms?) I need the standard errors and not the confidence intervals from an ARIMA fit. I can get fits: > coef(test) ar1 ma1 intercept time(TempVector) - 1900

Hello everyone, I'm doing some benchmark comparing Arima [1] and SVR on time series data. I'm using an out-of-sample one-step-ahead prediction from Arima using the "fitted" method [2]. Do someone know how to have a two-steps-ahead forecast timeseries from Arima? Thanks, Matteo Bertini [1] http://robjhyndman.com/software/forecast [2] AirPassengers example on page 5

I'm having a great deal of trouble replicating x12 ARIMA's F-test used to detect moving seasonality. According to all literature I could find, the test is apparently a 2-way ANOVA with year and month as factors for the SI ratios determined by x12's smoothing algorithm. Note the SI ratio is simply the detrended series. The summary I get from manually running this 2-way ANOVA using the

Dear R community, I have a project with electricity load forecasting, and I got hourly data for system load. If you haven't worked with electricity before, seasonality comes in many flavors: a daily pattern, with a peak at around 7pm; a weekly pattern, in which we use more electricity on weekdays in comparison to weekends; a winter-summer pattern, with air conditioning and heaters playing an

Hello, I using the fuction auto.arima() from package forecast to predict the values of p,d,q and P,D,Q. My problem is the execution time of this function, for example, a time series with 2323 values with seasonality to the week take over 8 hours to execute all the possibilities. I using a computer with Windows XP, a processor Intel Core2 Duo T7300 and 2Gb of RAM.

Hello R People: When using the arima function with the seasonal option, are the seasonal options only good for monthly and quarterly data, please? Also, I believe that weekly and daily data are not appropriate for seasonal parm estimation via arima. Is that correct, please? Thanks, Sincerely, Laura Holt mailto: lauraholt_983 at hotmail.com download!

Hi all, I just couldn't find a R function which can fit multiple seasonal patters... i.e. in the following code: *arima(x = data, order = c(p, d, q), seasonal = list(order = c(P, D, Q), period = S), ... *** * there can be only one "period", am I right? What if the data seem to have three different seasonality cycles, 5, 12, 21? Thanks a lot! * [[alternative HTML version

1. I have a R program in a file say "functions.R". I load the "functions.R" file the R using source("function.R") and then call functionsf1(), f2() etc. which are declared and defined within "function.R" file. I also need to load a couple of R libraries using library() before I can use f1(), f2() etc. My question is can I acheive all this (i.e. calling

Sir, I am a M.tech student of Computer Science and Engineering Department ,Indian Institute of technology, Kharagpur(India). I have to do a project in trusted computing field. I went through LLVM Project site. and I want to work in some project of LLVM. Can u suggest me some project which is somehow related to trusted computing and i can work on that ? In hope of your reply, Amit Suthar

Good evening! I have a question regarding forecast package and time series analysis. My syntax: x<-c(253, 252, 275, 275, 272, 254, 272, 252, 249, 300, 244, 258, 255, 285, 301, 278, 279, 304, 275, 276, 313, 292, 302, 322, 281, 298, 305, 295, 286, 327, 286, 270, 289, 293, 287, 267, 267, 288, 304, 273, 264, 254, 263, 265, 278) library(forecast) arima(x, order=c(1,1,2),

I was using tagPOS function from openNLP package for parts-of-speach. Now the package is updated and the function is not present. Any suggestions how to do it now ? Thanks for your help. -- Regards, Siddharth Arun, Contact No. - +91 8880065278 [[alternative HTML version deleted]]

m<-matrix(byrow=FALSE) t<-as.list(na.exclude(x)) j<-0 o<-0 for(i in 1:998) { d<- 5*(i-1)+3 if(t[[d]][[1]]>80) { j<-j+1 e[j]<-d l<-length(t[[d]]) u<-t[[d]] price_rand<-t[[d-1]] n<-0 for(k in 1:l) { if((u[k]>49)&&(u[k]<51)) { n<-n+1 m[n,j]<-price_rand[k] } } } } I am getting error in assigning the values to a matrix. *Error in m[n, j]

Hello, I'm using fArma package to estimate the value of Hurst exponent using R/S method. However, for a certain set of data I get H ~ 1.8. How do I interpret this? Following are the output that I get for this set: > mean(data[,2]) [1] 400.5433 > sd(data[,2]) [1] 1139.786 > > rsFit(data[,2], levels = 64) Title: Hurst Exponent from R/S Method Call: rsFit(x = data[, 2], levels

HI, there, When i use R, i tried to use function arima(), it complains: Error: couldn't find function "arima" But when I type "help.search("arima") ", I got arima() poped up.. arima(ts) ARIMA Modelling of Time Series arima.sim(ts) Simulate from an ARIMA Model arima0(ts) ARIMA Modelling of Time Series -- Preliminary

Hi, Does anyone know a method for adding a linear/polynominal trend to a simulated arima model using the arima.sim function? Any help will be greatly appreciated. Cheers, Sam.