similar to: Time series ARIMAX and multivariate models

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]]

I have just started using R for my PhD. I am importing my data from Excel via notepad into Word. Unfortunately, my data has many missing values. I have put '.' and this allowed me to import the data into R. However, I now want to interpolate these missing values. Please can someone give me some pointers as to the method/code I could use? Thankyou, Lillian.

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 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

Dear All, This is probably a very basic question but: I have plotted a map of the Barents Sea and surrounding coastline using: map('worldHires',ylim=c(50,85),xlim=c(5,65),fill=T,resolution=0) map.axes() map.scale(x=30,metric=T) Next, I imported a shapefile with depth contours for the sea: contours<-read.shape("D://My Documents/BarentsSea.shp",dbf.data=T) (This is in

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]]

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

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

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

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

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

I am trying to fit a generalised least squares model using gls in the nlme package. The model seems to fit very well when I plot the fitted values against the original values, and the model parameters have quite narrow confidence intervals (all are significant at p<5%). The problem is that the log likelihood is always given as -Inf. This doesn't seem to make sense because the model

On 1 Apr 2004 at 20:28, michele lux wrote: If by arimax you meant arima with the xreg argument, where xreg is a vector or matrix of exogeneous variables, then it is my understanding (but I did'nt yet understand the code completely) that the coefficients of the columns in xreg is estimate jointlt with the ARMA parameters, by maximum likelihood (or conditional maximum likelihood in the case

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 Team, I am running ARIMAX with TSA package. my code is fit2 <- arimax(yseries, order = c(1,0,1),xtransf = data.frame(X1var),transfer=list(c(1,0))) my question is 1st Q.--> If I need to take difference of X1var then what should i do?. What i am doing like submitting R code as X1vard <- diff(X1var) and then i am including in the xtransf. Same time if i need to take difference of

Hello! Recently I got report that my package mar1s doesn't pass checks any more on R 3.0.2. I started to investigate and found the following difference in multivariate time series handling in R 3.0.2 compared to R 2 (I've checked on 2.14.0). Suppose I wish to calculate seasonal component for time series. In case of multivariate time series, I wish to process each column independently.

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 ~ .

Hello, I have written code to plot an xyplot as follows: library(lattice) xyplot(len~ageJan1|as.factor(cohort),groups=sex,as.table=T,strip=strip.c ustom(bg='white',fg='white'),data=dat, xlab="Age (January 1st)",ylab="Length (cm)",main="Linear models for male and female cod, by cohort",type='p',

I'm trying to build a package. The machine is PowerPC G4 with Mac OS 10.4.8, and I'm using R2.4.1. I get "R CMD build roots" working, and it created roots.tar.gz. But I get the following message when I run "R CMD INSTALL -l ../myrlibrary roots.tar.gz" ====================================================================== * Installing *source* package 'roots'

Here is my problem: Autoregressive models are very interesting in forecasting consumptions (eg water, gas etc). Generally time series of this type have a long history with relatively simple patterns and can be useful to add external regressors for calendar events (holydays, vacations etc). arima() is a very powerful function but kalman filter is very slow (and I foun difficulties of estimation)