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 series
> summary(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.
Thank you,
b.
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