similar to: arima additive vs multiplicative seasonality

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

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 All, I've used the X-12-ARIMA or its earlier versions from S+ and R under both Unix and Windows platforms for many years using the klugey approach of calling an executable using in R the system function. I've found this serviceable for the following reasons. 1) Paul Gilbert's hunch is correct that many of the subroutines have extensive IO calls (especially the X-11 engine)

I've been trying to get comfy with arima() and associated functions in the ts() package. I'm thinking seriously about using this package, and R generally, in a 4th year intro time series course that I'm teaching this autumn. I have a couple of questions about arima: (1) The help file says that residuals component of the value returned by arima() consists of the

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 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!

I am using AUTO ARIMA for forecasting. But it is not detecting 'seasonality term' of its own for any data. Is there any other method by which we can detect seasonality and its frequency for any data? Is there any method through which seasonality and its frequency can be automatically detected from ACF plot? -- Siddharth Arun, 4th Year Undergraduate student Industrial Engineering and

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

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

Thanks for everyone's help with zoo -- I think I've got my data set ready. (The data consists of surface weather temperatures, from 2002 to 2005, one observation per hour. Some values are missing... i.e. NA) I have three goals: GOAL #1:Get the data in proper time series form, preserving frequency information: > w4.ts <- as.ts( w3.zoo, frequency=(1/3600) ) I hope that 1/3600

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, 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

To whom it may concern: I am trying to better understand the functionality of 'R' when making arima predictions to avoid any "Black Box" disadvantages. I'm fitting a seasonal arima model using the following command (having already loaded 'stat' package). arimaSeason <- arima(Data,order=c(1,0,1),seasonal=list(order=c(1,0,1),period=12)) I can then generate

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,

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

hallo to all I've to calculate an arima model and I need only the first and 365 th parameter and also the sar1 and the intercept, so I'm traing with: arima(X,order=c(365,0,0),seasonal=list(order=c(1,0,0),..),fixed=c(NA,rep(0,363),NA,NA,NA),transform.pars=F) but the error answer is: Error in polyroot(z) : polynomial degree too high (49 max) also there are problems in allocating memory

The following command crashes my Mac OS X version of R: (I'm running R on a PowerMac G5, with 1 GB of RAM and dual processors.) > arima.0 <- arima(w3.ts,order=c(1,0,0),seasonal=list(order=c (1,0,0),period=365)) -David Here is some background: w3.ts is hourly temperature data with about 20% NA's. It contains about 3.5 years of data. I am using period = 365, which makes

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]]

Hi, Is R's implementation of Seasonal ARIMA in the arima() function a multiplicative or an additive model? e.g., is an ARIMA(0,1,1)(0,1,1)[12] from arima() the same as Box et al's ARIMA(0,1,1)x(0,1,1)[12] (from Time Series Analysis 1994, p.333). From another post http://tolstoy.newcastle.edu.au/R/help/04/07/0117.html I suspect it's additive but I'm not sure. Thanks, Gad --

Dear R users, I need to to the the following. Let a= 1 2 3 4 5 6 and b= -1 -2 -3 be (2x3) matrices. -4 -5 -6 I need to combine the two matrices into a new (2x6) matrix like this: ab = ( 1 -1 2 -2 3 -3 ) 4 -4 5 -5 6 -6 How can this be done in R? ----------------------------------------------------------------- ?????? ???