On Thu, 31 Mar 2005, bogdan romocea wrote:
Dear useRs,
I want to simulate a time series (stationary; the distribution of values is skewed to the right; quite a few ARMA absolute standardized residuals above 2 - about 8% of them). Is this the right way to do it? #-------------------------------- load("rdtb") #the time seriessummary(rdtb)Min. 1st Qu. Median Mean 3rd Qu. Max. -1.11800 -0.65010 -0.09091 0.30390 1.12500 2.67600
farma <- arima(rdtb,order=c(1,0,1),include.mean=T)farma[["coef"]]ar1 ma1 intercept 0.58091575 0.02313803 0.30417062
sim <- list(NULL) #simulated for (i in 1:5) { sim[[i]] <- as.vector(arima.sim(list(ar=c(farma[["coef"]][1]), ma=c(farma[["coef"]][2])),n=length(rdtb),innov=rdtb)) } allsim <- as.data.frame(sim) colnames(allsim) <- paste("sim",1:5,sep="") all <- cbind(rdtb,allsim) #--------------------------------
I don't understand why the simulation runs generate virtually identical values:all[100:105,]rdtb sim1 sim2 sim3 sim4 sim5 100 2.3863636 1.065661 1.065661 1.065661 1.065661 1.065661 101 1.9318182 2.606093 2.606093 2.606093 2.606093 2.606093 102 2.2954545 3.854074 3.854074 3.854074 3.854074 3.854074 103 2.5882353 4.880240 4.880240 4.880240 4.880240 4.880240 104 2.0227273 4.917622 4.917622 4.917622 4.917622 4.917622 105 -0.1521739 2.751352 2.751352 2.751352 2.751352 2.751352
It appears I may be missing something (very) basic, but don't know what.
The meaning of `innovations'. The innovations determine the series, so you asked for the same series five times. In the reference, the innovations are e[t].
-- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595
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