Plotmo
isn't really meant for time-series models like arima models
and doesn't support them.
However, if you just want to plot the fitted model and some future
values, the following function will do it (there may be a simpler
way using the ts.plot function):
plarima <- function(ts, ..., n.ahead=1, main=deparse(substitute(ts)))
{
model <- arima(ts, ...)
if(!inherits(model, "Arima"))
stop("this function requires 'arima' from the standard stats package")
# calculations so we can extend the x axis
n <- length(ts)
x <- xy.coords(ts)$x
if(any(is.na(x)))
stop("NA in time")
xdelta <- (x[n] - x[1]) / n
plot(ts + model$residuals, # plot the fit in gray
xlim=c(x[1], x[n] + xdelta * n.ahead),
main=main, col="gray", lwd=3)
lines(ts) # plot the data
# predict n.ahead values and plot them in red
forecast <- predict(model, n.ahead=n.ahead)
lines(x=x[n] + xdelta * (0:n.ahead), y=c(ts[n], forecast$pred), col=2)
legend("topleft", legend=c("data", "fitted", "forecast"),
col=c(1, "gray", 2), lwd=c(1,3,1), lty=1, bg="white")
model # return the arima model
}
For example
plarima(lh, order=c(3,0,0), n.ahead=10)
plarima(USAccDeaths, order=c(0,1,1), seas=list(order=c(0,1,1)), n.ahead=10)
gives the following plots
(I'm assuming you are using the arima function from the
standard stats package. I think the forecast package also
has an arima function.)
