search for: estvarxls

Hello, Using the dse package I have estimated a VAR model using estVARXls(). I can perform forecasts using forecast() with no problems, but when I try to use simulate() with the same model, I get the following error: Error in diag(Cov, p) : 'nrow' or 'ncol' cannot be specified when 'x' is a matrix Can anyone shed some light on the meaning of t...

...106.0290, 106.0855, 106.1265, 106.1197, 106.1245, 106.1893, 106.2118, 106.1503, 106.0883, 106.0511, 106.0194, 106.0221) # Set TSdata object arma.fit.TSdata <- TSdata(input = arma.fit.input, output = arma.fit.output) # Fit the model arma.model.without.trend <- estVARXls(arma.fit.TSdata, max.lag=1, trend=F) arma.model.with.trend <- estVARXls(arma.fit.TSdata, max.lag=1, trend=T) # Apply the model for the test period arma.pred.TSdata <- TSdata(input = arma.pred.input, output = arma.pred.output[1:2]) arma.pred.without.trend <- forecast(TSmodel(arma.model....

Hi R-Community, so far I dealt with univariate processes and used the function "arima" to estimate an ARMA(1,1)-model. For multivariate processes there are the functions "estVARXar" and "estVARXls" from package "DSE". But how can I estimate an VARMA(1,1)-model, or even better determine the orders and estimate the parameters? Much thanks in advance, Hagen Schmoeller -- Dipl.-Ing. Hagen K. Schm??ller Leiter Forschungsgruppe Stromerzeugung und -handel Institut f??r Elektrische...

dear All, I have the following problem: I need to calculate an h-step ahead forecast from a var model (estimated with a dse1 method estVARXls), which in turn will be used as an input for another model as conditioning data, so I need it as a simple, numeric matrix. No exogenous input is used. However, the standard forecast method produces a 1-element list that includes a forecast matrix, yet I have no clue as to how to extract the values...

...January 1984 to December 2003, out-of-sample January 2004 to September 2009. This is what I have done at the moment betas<-read.table("C:\\Users\\Manta\\Desktop\\betas.txt",header=T,dec=",") BETA<-ts(betas,start=(1984),frequency=12) BETAS<-TSdata(output=BETA) VAR1<-estVARXls(window(BETAS,end=c(2003,12)),max.lag=1) pr<-forecast(VAR1,horizon=1) pr3<-forecast(VAR1,horizon=3) pr12<-forecast(VAR1,horizon=12) and the model is estimated correctly (same estimates as found using other softwares) Then the tricky part: I want to estimate the betas for January 2004, Marc...

...and a seasonality. (but the serie is stationary) I use the VAR function from the package vars, but after red the package's guide, I'm not sure if this function could estimate a model for this kind of serie (trend + seasonality), and it is important for the forecast. I also use the function estVARXls from the package dse but the results are strange. The second problem is that I have to use the future promotion to make the forecast; the var function can give me a forecast for the sales, but I don't know if we can seize the future promotions (that I know and which I have) in the function (pr...

Hi all, I'm looking for R packages that estimate multivariate time-series models or vector-autoregression (VAR) time-series models. Thanks David -- =========================================================================== David Kaplan, Ph.D. Professor Department of Educational Psychology University of Wisconsin - Madison Educational Sciences, Room, 1061 1025 W. Johnson Street Madison,

Hello to everyone! I have a question for you..I need to predict multivariate time series, for example sales of 2 products related one to the other, having the 2 prices like inputs.. Is there in R a function to do it? I saw dse package but I didn't find what a I'm looking for.. Could anyone help me? Thank you very much Giusy -- View this message in context: