AirPassengers {datasets} | R Documentation |
The classic Box & Jenkins airline data. Monthly totals of international airline passengers, 1949 to 1960.
AirPassengers
A monthly time series, in thousands.
Box, G. E. P., Jenkins, G. M. and Reinsel, G. C. (1976) Time Series Analysis, Forecasting and Control. Third Edition. Holden-Day. Series G.
## Not run: ## These are quite slow and so not run by example(AirPassengers) ## The classic 'airline model', by full ML (fit <- arima(log10(AirPassengers), c(0, 1, 1), seasonal = list(order=c(0, 1 ,1), period=12))) update(fit, method = "CSS") update(fit, x=window(log10(AirPassengers), start = 1954)) pred <- predict(fit, n.ahead = 24) tl <- pred$pred - 1.96 * pred$se tu <- pred$pred + 1.96 * pred$se ts.plot(AirPassengers, 10^tl, 10^tu, log = "y", lty = c(1,2,2)) ## full ML fit is the same if the series is reversed, CSS fit is not ap0 <- rev(log10(AirPassengers)) attributes(ap0) <- attributes(AirPassengers) arima(ap0, c(0, 1, 1), seasonal = list(order=c(0, 1 ,1), period=12)) arima(ap0, c(0, 1, 1), seasonal = list(order=c(0, 1 ,1), period=12), method = "CSS") ## Structural Time Series ap <- log10(AirPassengers) - 2 (fit <- StructTS(ap, type= "BSM")) par(mfrow=c(1,2)) plot(cbind(ap, fitted(fit)), plot.type = "single") plot(cbind(ap, tsSmooth(fit)), plot.type = "single") ## End(Not run)