plot.forecast: Forecast plot
In forecast: Forecasting Functions for Time Series and Linear Models

plot.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 `forecast`.
`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 `showgap=FALSE`, the gap between the historical observations and the forecasts is removed.
`shaded`	Logical flag indicating whether prediction intervals should be shaded (`TRUE`) or lines (`FALSE`)
`shadebars`	Logical flag indicating if prediction intervals should be plotted as shaded bars (if `TRUE`) or a shaded polygon (if `FALSE`). Ignored if `shaded=FALSE`. Bars are plotted by default if there are fewer than five forecast horizons.
`shadecols`	Colors for shaded prediction intervals. To get default colors used prior to v3.26, set `shadecols="oldstyle"`.
`col`	Colour for the data line.
`fcol`	Colour for the forecast line.
`pi.col`	If `shaded=FALSE` and `PI=TRUE`, the prediction intervals are plotted in this colour.
`pi.lty`	If `shaded=FALSE` and `PI=TRUE`, the prediction intervals are plotted using this line type.
`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 `plot.default`.
`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 `forecast`. Used for ggplot graphics (S3 method consistency).
`series`	Matches an unidentified forecast layer with a coloured object on the plot.
`fitcol`	Line colour for fitted values.
`pch`	Plotting character (if `type=="p"` or `type=="o"`).

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/

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)

forecast documentation built on June 22, 2024, 9:20 a.m.