class(x)[1] = ftsm
, plot showing the principal components in the top row of plots and the coefficients in the bottom row of plots.When class(x)[1] = fm
, plot showing the predictor scores in the top row of plots and the response loadings in the bottom row of plots.
"plot"(x, order, xlab1 = x$y$xname, ylab1 = "Principal component", xlab2 = "Time", ylab2 = "Coefficient", mean.lab = "Mean", level.lab = "Level", main.title = "Main effects", interaction.title = "Interaction", basiscol = 1, coeffcol = 1, outlier.col = 2, outlier.pch = 19, outlier.cex = 0.5, ...)
plot.type = "components"
.plot.type = "components"
.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.
ftsm
, forecast.ftsm
, residuals.fm
, summary.fm
, plot.fmres
, plot.ftsf