Plot Forecasts with Trellis Graphics

Plot forecasts from forecast::forecast(). It is built mostly to resemble the forecast::autoplot.forecast() and forecast::plot.forecast() functions, but in addition tries to plot the predictions on the original scale.

# S3 method for forecast
xyplot(x, data = NULL, ci = TRUE, ci_levels = x$level,
  ci_key = ci, ci_pal = hcl(0, 0, 45:100),
  ci_alpha = trellis.par.get("regions")$alpha, ...)

Arguments

x	An object of class forecast.
data	Data of observations left out of the model fit, usually "future" observations.
ci	Plot confidence intervals for the predictions.
ci_levels	The prediction levels to plot as a subset of those forecasted in x.
ci_key	Set to TRUE to draw a key automatically or provide a list (if length(ci_levels) > 5 should work with lattice::draw.colorkey() and otherwise with lattice::draw.key())
ci_pal	Color palette for the confidence bands.
ci_alpha	Fill alpha for the confidence interval.
...	Arguments passed on to lattice::panel.xyplot().

Value

An object of class "trellis". The update method can be used to update components of the object and the print method (usually called by default) will plot it on an appropriate plotting device.

Details

This function requires the zoo package.

See also

lattice::panel.xyplot(), forecast::forecast(), lattice::xyplot.ts().

Examples

if (require(forecast)) {
  train <- window(USAccDeaths, c(1973, 1), c(1977, 12))
  test <- window(USAccDeaths, c(1978, 1), c(1978, 12))
  fit <- arima(train, order = c(0, 1, 1),
               seasonal = list(order = c(0, 1, 1)))
  fcast1 <- forecast(fit, 12)
  xyplot(fcast1, test, grid = TRUE, auto.key = list(corner = c(0, 0.99)),
         ci_key = list(title = "PI Level"))

  # A fan plot
  fcast2 <- forecast(fit, 12, level = seq(0, 95, 10))
  xyplot(fcast2, test, ci_pal = heat.colors(100))
}
#> Loading required package: forecast