plot.ftsm | R Documentation |
Plot showing the basis functions in the top row of plots and the coefficients in the bottom row of plots.
## S3 method for class 'ftsm'
plot(x, components, components.start = 0, xlab1 = x$y$xname, ylab1 = "Basis function",
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, ...)
x |
Output from |
components |
Number of principal components to plot. |
components.start |
Plotting specified component. |
xlab1 |
x-axis label for basis functions. |
xlab2 |
x-axis label for coefficient time series. |
ylab1 |
y-axis label for basis functions. |
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. |
basiscol |
Colors for basis functions if plot.type="components". |
coeffcol |
Colors for time series coefficients if plot.type="components". |
outlier.col |
Colour for outlying years. |
outlier.pch |
Plotting character for outlying years. |
outlier.cex |
Size of plotting character for outlying years. |
... |
Plotting parameters. |
None. Function produces a plot.
Rob J Hyndman
R. J. Hyndman and M. S. Ullah (2007) "Robust forecasting of mortality and fertility rates: A functional data approach", Computational Statistics and Data Analysis, 51(10), 4942-4956.
R. J. Hyndman and H. L. Shang (2009) "Forecasting functional time series" (with discussion), Journal of the Korean Statistical Society, 38(3), 199-221.
forecast.ftsm
, ftsm
, plot.fm
, plot.ftsf
, residuals.fm
, summary.fm
# plot different principal components.
plot.ftsm(ftsm(y = ElNino_ERSST_region_1and2, order = 2), components = 2)
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