| plot.forecast {forecast} | R Documentation | 
Forecast plot
Description
Plots historical data with forecasts and prediction intervals.
Usage
## S3 method for class 'forecast'
plot(
  x,
  include,
  PI = TRUE,
  showgap = TRUE,
  shaded = TRUE,
  shadebars = (length(x$mean) < 5),
  shadecols = NULL,
  col = 1,
  fcol = 4,
  pi.col = 1,
  pi.lty = 2,
  ylim = NULL,
  main = NULL,
  xlab = "",
  ylab = "",
  type = "l",
  flty = 1,
  flwd = 2,
  ...
)
## S3 method for class 'forecast'
autoplot(
  object,
  include,
  PI = TRUE,
  shadecols = c("#596DD5", "#D5DBFF"),
  fcol = "#0000AA",
  flwd = 0.5,
  ...
)
## S3 method for class 'splineforecast'
autoplot(object, PI = TRUE, ...)
## S3 method for class 'forecast'
autolayer(object, series = NULL, PI = TRUE, showgap = TRUE, ...)
## S3 method for class 'splineforecast'
plot(x, fitcol = 2, type = "o", pch = 19, ...)
Arguments
| x | Forecast object produced by  | 
| include | number of values from time series to include in plot. Default is all values. | 
| PI | Logical flag indicating whether to plot prediction intervals. | 
| showgap | If  | 
| shaded | Logical flag indicating whether prediction intervals should be
shaded ( | 
| shadebars | Logical flag indicating if prediction intervals should be
plotted as shaded bars (if  | 
| shadecols | Colors for shaded prediction intervals. To get default
colors used prior to v3.26, set  | 
| col | Colour for the data line. | 
| fcol | Colour for the forecast line. | 
| pi.col | If  | 
| pi.lty | If  | 
| ylim | Limits on y-axis. | 
| main | Main title. | 
| xlab | X-axis label. | 
| ylab | Y-axis label. | 
| type | 1-character string giving the type of plot desired. As for
 | 
| flty | Line type for the forecast line. | 
| flwd | Line width for the forecast line. | 
| ... | Other plotting parameters to affect the plot. | 
| object | Forecast object produced by  | 
| series | Matches an unidentified forecast layer with a coloured object on the plot. | 
| fitcol | Line colour for fitted values. | 
| pch | Plotting character (if  | 
Details
autoplot will produce a ggplot object.
plot.splineforecast autoplot.splineforecast
Value
None.
Author(s)
Rob J Hyndman & Mitchell O'Hara-Wild
References
Hyndman and Athanasopoulos (2018) Forecasting: principles and practice, 2nd edition, OTexts: Melbourne, Australia. https://otexts.com/fpp2/
See Also
Examples
library(ggplot2)
wine.fit <- hw(wineind,h=48)
plot(wine.fit)
autoplot(wine.fit)
fit <- tslm(wineind ~ fourier(wineind,4))
fcast <- forecast(fit, newdata=data.frame(fourier(wineind,4,20)))
autoplot(fcast)
fcast <- splinef(airmiles,h=5)
plot(fcast)
autoplot(fcast)