ftsa (version 6.4)

residuals.fm: Compute residuals from a functional model

Description

After fitting a functional model, it is useful to inspect the residuals. This function extracts the relevant information from the fit object and puts it in a form suitable for plotting with image, persp, contour, filled.contour, etc.

Usage

# S3 method for fm
residuals(object, ...)

Value

Produces an object of class “fmres” containing the residuals from the model.

Arguments

object

Output from ftsm or fplsr.

...

Other arguments.

Author

Rob J Hyndman

References

B. Erbas and R. J. Hyndman and D. M. Gertig (2007) "Forecasting age-specific breast cancer mortality using functional data model", Statistics in Medicine, 26(2), 458-470.

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.

H. L. Shang (2012) "Point and interval forecasts of age-specific fertility rates: a comparison of functional principal component methods", Journal of Population Research, 29(3), 249-267.

H. L. Shang (2012) "Point and interval forecasts of age-specific life expectancies: a model averaging", Demographic Research, 27, 593-644.

See Also

ftsm, forecast.ftsm, summary.fm, plot.fm, plot.fmres

Examples

plot(residuals(object = ftsm(y = ElNino_ERSST_region_1and2)), 
	xlab = "Year", ylab = "Month")