similar to: Estimation and Forecast of Seasonal Component

Dear all, I stumbled upon what appears to be a troublesome issue when sampling from an ARIMA model (from Rob Hyndman's excellent 'forecast' package) that contains a seasonal AR component. Here's how to reproduce the issue. (I'm using R 2.9.2 with forecast 2.19; see sessionInfo() below). First some data: > x <- c( 0.132475, 0.143119, 0.108104, 0.247291, 0.029510,

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

Hi All, a) Is it possible to estimate the strength of seasonality in timeseries data. Say I have monthly mean prices of an ten different assets. I decompose the data using stl() and obtain the seasonal parameter for each month. Is it possible to order the assets based on the strength of seasonality? b) which gives a better estimate on seasonality stl() or a robust linear model like

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 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 everybody, I am currently trying to forecast some double seasonal time series by using the function dshw. I want to access the standard errors to build the confident interval for my forecast. I am using to following code : fit<-dshw(eem,period1=7,period2=48,h=48) then by using summary(fit), I see that my se are contained in the vector : $s20 but when I call fit$s20, I get NULL. I

> It might clarify your thinking to note that a seasonal ARIMA model > is just an ``ordinary'' ARIMA model with some coefficients > constrained to be 0 in an efficient way. E.g. a seasonal AR(1) s = > 4 model is the same as an ordinary (nonseasonal) AR(4) model with > coefficients theta_1, theta_2, and theta_3 constrained to be 0. You > can get the same answer as from

Hello, does anyone know about: a) simulating seasonal ARIMA models? arima out of package ts can fit it, but it does not look like it can simulates data from seasonal models b) fitting and simulating fractional seasonal ARIMA models? Hints will be appreciated, Henning -- Henning Rust Potsdam Institute for Climate Impact Research Dept. Integrated Systems Analysis Tel.: #49/331/288-2596

Hi all, I was wondering how to construct a seasonal differenced time series variable. I used the following code to construct a 12 span seasonal difference seasonal<-diff(V2, lag=12, differences=1) is this correct? thank you in advance joe [[alternative HTML version deleted]]

Hello everybody, I need to calculate seasonal means with temperature data for my work. I have 70 files coming from weather stations, which looks like this for example: startdate <- as.POSIXct("01/01/2006", format = "%d/%m/%Y") enddate <- as.POSIXct("05/01/2006", format = "%d/%m/%Y") date <- seq(from = startdate, to = enddate, by =

I'm trying to use the following command. arima (x, order = c(p,d,q), seasonal =list(order=c(P,D,Q), period=s) How can I write an estimated seasonal ARIMA model from the outputs. To be specifically, which sign to use? I know R uses a different signs from S plus. Is it correct that the model is: (1-ar1*B-ar2*B^2-...)(1-sar1*B^s-sar2*B^2s-....)(1-B)^d(1-B^s)^D

Hello, I am new to usin R - which is a great tool - and would like to know if R has a seasonal adjustment program for time series and/if it incorporates the Census Bureau's ARIMA x-12 seasonal adjustment program in any way? Thanks so much! Tony [[alternative HTML version deleted]]

Hello All, I trying to find some way to fill in missing values in a seasonal time series. All the function that I find until now, don't have any reference to seasonal data and the output is very different of what I looking for. I also searched the forum but this problem don't have many information or people asking. Could someone indicate some links or packages related to this question?

Are any seasonal adjustment programs, like Tramo/Seats, Census X12 ARIMA or Berliner Verfahren implemented in R? I am doing a simulation study and I don't know how to adjust the series in R. The possibility to access external the exe.files of the seasonal adjustment programs seems to be quite difficult. Can anyone help me? Thanks, Ingo

Hi, I tried to use the Croston function from the forecasting package 1.24<http://robjhyndman.com/software/forecasting> with the code below, but I get in return this message "*Error in decompose(ts(x[1L:wind], start = start(x), frequency = f), seasonal) : time series has no or less than 2 periods*". histValues

Hello All, I trying to use the function auto.arima(....) from package forecast but I have a problem. My steps after I used the function auto.arima(...) I create the time series like this: >bbrass = scan("C:/Program Files/R/data PTIN/my_file.dat") >regts.start = ISOdatetime(2006, 7, 1, hour=0, min=0, sec=0, tz="GMT") #2006 07 01 00 >regts.end = ISOdatetime(2006, 7,

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

Hello, I have daily wind speed data and need to fit seasonal ARIMA model, problem is that my period is 365. But when I use arima(...) function, with period 365, I?m getting error message: ?Error in makeARIMA(trarma[[1]], trarma[[2]], Delta, kappa) : maximum supported lag is 350?. Can someone help me with this problem? Thank you Sincerely yours, Laura Saltyte

Hi all, First: I have a small line of code I'm applying to a variable which will be placed in a matrix table for latex output of accuracy measures: acc.aarima <- signif(accuracy(forecast(auto.arima(tix_ts, stepwise=FALSE), h=365)), digits=3). The time series referred to is univariate (daily counts from 12-10-2010 until 5-8-2010 (so not 2 full periods of data)), and I'm working on

Dear R users, I would like to construct a matrix of seasonal dummy variables, such matrix can be written as follows(i.e format(T,4)) 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 . . . . . . . . etc I have written the following small program: