AirPassengers {datasets} | R Documentation

## Monthly Airline Passenger Numbers 1949-1960

### Description

The classic Box & Jenkins airline data. Monthly totals of international airline passengers, 1949 to 1960.

### Usage

    AirPassengers

### Format

A monthly time series, in thousands.

### Source

Box, G. E. P., Jenkins, G. M. and Reinsel, G. C. (1976) Time Series Analysis, Forecasting and Control. Third Edition. Holden-Day. Series G.

### Examples

    ## 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)

[Package datasets version 3.3.2 Index]