plot.ftsf {ftsa}R Documentation

Plot fitted model components for a functional time series model

Description

Plot fitted model components for a fts object.

Usage

plot.ftsf(x, plot.type = c("function", "components", "variance"), 
 components, xlab1 = fit$y$xname, ylab1 = "Principal component", 
  xlab2 = "Time", ylab2 = "Coefficient", mean.lab = "Mean", 
   level.lab = "Level", main.title = "Main effects", 
    interaction.title = "Interaction", vcol = 1:3, shadecols = 7, 
     fcol = 4, basiscol = 1, coeffcol = 1, outlier.col = 2,
      outlier.pch = 19, outlier.cex = 0.5,...)

Arguments

x Output from forecast.ftsm.
plot.type Type of plot.
components Number of principal components.
xlab1 x-axis label for principal components.
xlab2 x-axis label for coefficient time series.
ylab1 y-axis label for principal components.
ylab2 y-axis label for coefficient time series.
mean.lab Label for mean component.
level.lab Label for level component.
main.title Title for main effects.
interaction.title Title for interaction terms.
vcol Colors to use if plot.type = "variance".
shadecols Color for shading of prediction intervals when plot.type = "components".
fcol Color of point forecasts when plot.type = "components".
basiscol Colors for principal components if plot.type = "components".
coeffcol Colors for time series coefficients if plot.type = "components".
outlier.col Colors for outlying years.
outlier.pch Plotting character for outlying years.
outlier.cex Size of plotting character for outlying years.
... Plotting parameters.

Details

When plot.type = "function", it produces a plot of the forecast functions;

When plot.type = "components", it produces a plot of the principla components and coefficients with forecasts and prediction intervals for each coefficient;

When plot.type = "variance", it produces a plot of the variance components.

Value

Function produces a plot.

Author(s)

Rob J Hyndman

References

R. J. Hyndman and M. S. Ullah (2007) "Robust forecasting of mortality and fertility rates: A functional data approach", Computational Statistics & Data Analysis, 51(10), 4942-4956.

R. J. Hyndman and H. Booth (2008) "Stochastic population forecasts using functional data models for mortality, fertility and migration", International Journal of Forecasting, 24(3), 323-342.

R. J. Hyndman and H. L. Shang (2009) "Forecasting functional time series (with discussion)", Journal of the Korean Statistical Society, 38(3), 199-221.

See Also

ftsm, plot.fm, plot.fmres, residuals.fm, summary.fm

Examples

plot(x = forecast(object = ftsm(y = ElNino)))

[Package ftsa version 1.3 Index]