Plot fitted model components for a functional time series model
Plot fitted model components for a fts object.
## S3 method for class 'ftsf'
plot(x, plot.type = c("function", "components", "variance"),
components, xlab1 = fit$y$xname, ylab1 = "Basis function",
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,...)x |
Output from |
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 |
shadecols |
Color for shading of prediction intervals when |
fcol |
Color of point forecasts when |
basiscol |
Colors for principal components if |
coeffcol |
Colors for time series coefficients if |
outlier.col |
Colors for outlying years. |
outlier.pch |
Plotting character for outlying years. |
outlier.cex |
Size of plotting character for outlying years. |
... |
Plotting parameters. |
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.
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. 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.
H. L. Shang, H. Booth and R. J. Hyndman (2011) "Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods", Demographic Research, 25(5), 173-214.
plot(x = forecast(object = ftsm(y = ElNino_ERSST_region_1and2)))
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