similar to: RE. arimaX

Hallo all can someone explain me how the exogenus variables work in the arimax models is not clear for me... Thanks Michele

Hi R Users, I'm fairly new to R (about 3 months use thus far.) I wanting to use the arimax function from the TSA library to incorporate some exogenous inputs into the basic underllying arima model.Then with that newly model of type arimax, I would like to make a prediction. To avoid being bogged down with issues specific to my own work, I would like to refer to readers to the example

Dear list members, I am a (very) recent convert to R and I am hoping you can help me with a problem I'm having. I'm trying to fit a first-order transfer function to an ARIMA intervention analysis using the "arimax" function. The data was obtained from McCleary & Hay (1980) (via Rob Hyndman's Time Series Library: http://robjhyndman.com/tsdldata/data/schizo.dat). It has

Dear R-helpers, I would appreicate if someone can help me on the transfer parameter in ARIMAX and also see what I am doing is correct. I am using ARIMAX with 2 Exogeneous Variables and 10 years data are as follows: DepVar Period, depVar, IndepVar1 Period, indepVar1, IndepVar2 Period, indepVar2 Jan 1998,708,Jan 1998,495,Jan 1998,245.490 Feb 1998,670,Feb 1998,421.25,Feb 1998,288.170 Mar

Hi R team, We?ve run Arimax models in R. We had a lot of queries around the interpretation of the outputs. *Dependent variable =* Volume (Growth %) *Independent Variables =* 3 Macroeconomic variables (Growth %) Following is the line of code Arimax.Model <- auto.arima(y = input.data[,"Volume"], xreg = input.data[,model.vars], seasonal = F) Following is the output

Hi I'm trying to measure the effect of a policy intervention (Box and Tiao, 1975). This query has to do with the coding of the model rather than with the particulars of my dataset, so I'm not providing the actual dataset (or a simulated one) in this case, apart from some general description. The time series are of length n=34 (annual observations between 1977 and 2010). The policy

Dear ALL, I would appreciate if someone help me by letting me know the code of above model in R.I would request you to please let me know how i could make arimax model in auto.arima. Regards Ramanath [[alternative HTML version deleted]]

Forescasting using predict() in an object of class arimax when there is an outlier IO in the model. Hi R users I have a problem when a use the predict() method in an object of class arimax ( These objects are the results of the implementation of the function arimax() from the TSA library) . The object is a model of a time series in which I identified an IO oulier at the element 33 of the serie

Dear all, I am fitting an arimax (arima with some extra explanatory variables) model to a time series. Say, I have a Y (dependent variable) and an X (explanatory). Y is 100 observations (time series) and X is 100 + 20 (20 to use for the forecast horizon). I can not make xreg work with the forecast function for an arima fit. The "predict" function seems to be working but the

to clean up some code I would like to make a list of arbitrary length to store?various objects for use in a loop sample code: ############ BEGIN SAMPLE ############## # You can see the need for a loop already linearModel1=lm(modelSource ~ .,mcReg) linearModel2=step(linearModel1) linearModel3=lm(modelSource ~ .-1,mcReg) linearModel4=step(linearModel3) #custom linearModel5=lm(modelSource ~ .

Dear Lillian, I would request you if you provide me the knowledge of how build ARIMAX model in R? It would be great help for me. Thanks Ramanath [[alternative HTML version deleted]]

Dear List, The purpose of this e-mail is to ask about R time series procedures - as a biologist with only basic time series knowledge and about a year's experience in R. I have been using ARIMAX models with seasonal components on seasonal data. However I am now moving on to annual data (with only 34 time points) and understand that ARIMA is not suitable for these shorter time periods - does

Hola! I got problems using an objects returned from arima (in KalmanSmooth(my.ts, ModArima$model), because my.ts showed up to have storage mode "integer" (is.integer(my.ts was TRUE). Should storage.mode() of a ts be allowed to be integer, should ts() someplace say storage.mode(ts.out) <- "double", or maybe inside arima() storage.mode(x) <- "double"

I've posted this before but have not been able to locate what I'm doing wrong. I cannot determine how the forecast is made using the estimated coefficients from a simple AR(2) model when there is an exogenous variable. Does anyone know what the problem is? The help file for arima doesn't show the model with any exogenous variables. I haven't been able to locate any documents

As I am reading ?arima, only NA entries in the argument fixed= imports. The following seems to indicate otherwise: x <- arima.sim(model=list(ar=0.8), n=100) + (1:100)/50 > t <- 1:100 > mod1 <- lm(x ~ t) > > init1 <- c(0, coef(mod1)[2]) > fixed1 <- c(as.numeric(NA), 0) > > arima(x, order=c(1,0,0), xreg=t, include.mean=FALSE, init=init1, fixed=fixed1)

I'm using the arima function to estimate coefficients and also using predict.Arima to forecast. This works nicely and I can see that the results are the same as using SAS's proc arima. I can also take the coefficent estimates for a simple model like ARIMA(2,1,0) and manually compute the forecast. The results agree to 5 or 6 decimal places. I can do this for models with and without

Hello all, I have been using R's time series capabilities to perform analysis for quite some time now and I am having some questions regarding its reliability. In several cases I have had substantial disagreement between R and other packages (such as gretl and the commercial EViews package). I have just encountered another problem and thought I'd post it to the list. In this case,

Hello, I am a beginner user of R and I would like to estimate a model with AR errors. I use arima function: modele <-arima(conso,xreg=var.exogenes,order=c(ordre,0,0),include.mean=TRUE,method ="CSS") My inputs are dummies for each month except one, and the same thing for each day and each hour. I have this error message: Warning message: possible convergence problem: optim gave

I am new to R-system. I have found time series modeling package whereby ARIMA model can be developed. I would like to know if there exists some package within R-system whereby parameters of transfer function model can be estimated using the preliminaraly identified model. Any sort of help in this regard will be highly appreciated. MG __________________________________________________ Do You

Hi, I am brand new to R and not familiar with the language, though I have been reading the manuals and making some slow going progress. I am working with some source code from a Global Vector Auto -Regressive program written by Ranier Puhr from the R-forge group. I need help interpreting the processes of the following code. I am going to post in parts since it's pretty long: GVAR