I want to simulate ARIMA(1,1,0)
with varying:
- sample sizes
- phi values
- standard deviation values.
I admire how the bellow r
code is simulating just one ARIMA(1,1,0)
which I want to follow the format to simulate many ARIMA(1,1,0)
with varying sample sizes, phi values and standard deviation values
wn <- rnorm(10, mean = 0, sd = 1)
ar <- wn[1:2]
for (i in 3:10){
ar<- arima.sim(n=10,model=list(ar=-0.7048,order=c(1,1,0)),start.innov=4.1,n.start=1,innov=wn)
}
I have asked a similar question here and given a good answer based on my question, but now I see that arima.sim()
function is indispensable in simulating ARIMA
time series and therefore want to incorporate it into my style of simulating ARIMA
time series.
I come up with this trial that uses arima.sim()
function to simulate N=c(15, 20) ARIMA(1,1,0)
time series with varying sample sizes, standard deviation values and phi values by first generating N random number and then using the initial two random number to be the first two ARIMA(1,1,0). The 3rd to **n**th are the made to follow
ARIMA(1,1,0)`.
Here is what I have tried bellow:
N <- c(15L, 20L)
SD = c(1, 2) ^ 2
phi = c(0.2, 0.4)
res <- vector('list', length(N))
names(res) <- paste('N', N, sep = '_')
set.seed(123L)
for (i in seq_along(N)){
res[[i]] <- vector('list', length(SD))
names(res[[i]]) <- paste('SD', SD, sep = '_')
ma <- matrix(NA_real_, nrow = N[i], ncol = length(phi))
for (j in seq_along(SD)){
wn <- rnorm(N[i], mean = 0, sd = SD[j])
ar[[1:2, ]] <- wn[[1:2]]
for (k in 3:N[i]){
ar[k, ] <- arima.sim(n=N[[i]],model=list(ar=phi[[k]],order=c(1,1,0)),start.innov=4.1,n.start=1,innov=wn)
}
colnames(ar) <- paste('ar_theta', phi, sep = '_')
res[[i]][[j]] <- ar
}
}
res1 <- lapply(res, function(dat) do.call(cbind, dat))
sapply(names(res1), function(nm) write.csv(res1[[nm]],
file = paste0(nm, ".csv"), row.names = FALSE, quote = FALSE))
The last two lines write the time series data in .csv and save it in my working directory.