search for: undifferencing

...e bottom of this note. The steps include (1) an initial linear regression model, (2) building an ARIMA model, (3) creating 12 months of simulated 'real' data - for various values of projected changes in slope from the linear regression - from the ARIMA model using arima.sim with subsequent undifferencing and appending to historical data, (3) one-step-ahead forecasting for 12 months using the 'fixed' arima model and simulated data, (4) taking the residuals from the forecasting (simulated minus forecast for each of the 12 months) and applying QC charting, and (5) counting the number (if any)...

Hi, All, This is my program ts1.sim <- arima.sim(list(order = c(1,1,0), ar = c(0.7)), n = 200) ts2.sim <- arima.sim(list(order = c(1,1,0), ar = c(0.5)), n = 200) tdata<-ts(c(ts1.sim[-1],ts2.sim[-1])) tre<-c(rep(0,200),rep(1,200)) gender<-rbinom(400,1,.5) x<-matrix(0,2,400) x[1,]<-tre x[2,]<-gender fit <- arima(tdata, c(1, 1, 0), method = "CSS",xreg=t(x))

Folks, I have been using the VAR {vars} program to find a fit for the following bi-variate time series (subset): bivariateTS<-structure(c(0.950415958293559, 0.96077848972081, 0.964348957109053, 0.967852884998915, 0.967773510751625, 0.970342843688257, 0.97613937178359, 0.980118627997436, 0.987059493773907, 0.99536830931504, 1.00622672085718, 1.01198013845981, 1.01866618122606,