forecastLSW (version 1.0)

plot: Plot the results of forecasting using forecastlpacf

Description

The forecastlpacf performs forecasting on a locally stationary (wavelet) time series. This function provides several options to plot the results in a user-friendly fashion.

Usage

# S3 method for forecastlpacf
plot(x, extra.y = NULL, f.col = 4, show.pi = "standard", 
    pi.col = 2, xlab = "Time", ylab = "Time Series", zoom = FALSE, zoom.no = 30, 
    sw = 0.2, conf.level = 95, pc.fan = (1:9) * 10, fan.seps = FALSE, 
    fan.rgb.col=c(1,0,0), ...)

Value

The function only returns information if show.pi="fan". In this case an array is returned that contained the coordinates of the fan part of the plot. The array is three-dimensional. Dimension 1 corresponds to the number of steps ahead that we computed for the forecast in the object x, dimension 2 corresponds to the number of fan prediction intervals specified by the number of confidence bands in pc.fan, dimension 3 always has two dimensions: 1 corresponding to the upper prediction interval and 2 correspond to the lower interval. For example, element[2, 3, 1] corresponds to the upper prediction interval, for the fan component associated with the third fan confidence level value in pc.fan

for the h=2 step ahead forecast.

Arguments

x

The object returned by the forecastlpacf function.

extra.y

Sometimes other routines wish to add to the plot generated by this function. The y-axis extent of those extra values might be larger than the values that this plot alone would generate. So, you can use this argument to provide a set of y-values that you want to later plot and this plot takes those into account when setting the scale of the y-axis. So, if you have extra characters or lines to plot after this plot, and you want to ensure they'll get plotted and that the y-axis is going to be large enough, supply the y values as a vector (or just their maximum and minimum) and this function will use them to help set the y-axis scale.

f.col

The colour used to drae the forecasted values - both the points and line joining the forecasts.

show.pi

If set to "standard" then 100*conf.level percent prediction intervals are drawn for each forecasted point in the colour specified by pi.col. If set to "none" then no prediction intervals are drawn. If set to "fan" then a Bank-of-England-like fan-plot is produced with confidence levels set by the pc.fan argument.

pi.col

Colour of the prediction intervals or fan plot.

xlab

The x-axis label.

ylab

The y-axis label.

zoom

Sometimes for a long time series with a few forecasts the forecast values can be hard to see and particularly how they relate to the values of the series near to the end of the series. If TRUE then this argument causes the function to only plot the last zoom.no values of the time series and the associated forecasts. One can then focus on the end of the time series nearer to the forecast values and those values. If FALSE then the whole time series and the forecasts are plotted and zoom.no is ignored.

zoom.no

The number of time series values plotted if zoom=TRUE.

sw

The width of the prediction intervals if show.pi="standard".

conf.level

A single confidence value associated with the prediction interval expressed as a numerical value from 0-100.

pc.fan

A vector of confidence values associated with the fan plot prediction intervals expressed as a percentage.

fan.seps

If TRUE then lines are drawn on the fan part of the fan plot to more clearly indicated the distinction between different prediction intervals. If FALSE then no extra lines are drawn.

fan.rgb.col

A vector of length three containing the red, green and blue intensities of the fan plot colour

...

Other arguments to plot.

Author

Guy Nason

Details

This function produces a plot of a time series and its forecasts generated by the forecastlpacf function.

References

Killick, R., Knight, M.I., Nason, G.P., Nunes M.A., Eckley I.A. (2023) Automatic Locally Stationary Time Series Forecasting with application to predicting U.K. Gross Value Added Time Series under sudden shocks caused by the COVID pandemic arXiv:2303.07772

See Also

forecastlpacf

Examples

#
# Simulate an example
#
x.test <- tvar2sim()
#
# Do a two-step ahead forecast
#
x.fl <- forecastlpacf(x.test, h=2, forecast.type="recursive")
#
# Now plot it.
#
# zoom=TRUE: so we only plot the last 30 time series observations, by default
# 	change zoom.no if you want more or less.
# f.col=3: the forecasts and connecting lines are drawn in colour 3 (blue)
# show.pi="fan": do a fan chart for the forecasts
# fan.rgb.col=c(1,0,1):	draw the fan in magenta (default is red)
# ylab="My Time Series": change the y label to something nice
#
plot(x.fl,zoom=TRUE, f.col=3, show.pi="fan", fan.rgb.col=c(1,0,1), ylab="My Time Series")