forecastfplsr: Forecast functional time series

In ftsa: Functional Time Series Analysis

Forecast functional time series

Description

The decentralized response is forecasted by multiplying the estimated regression coefficient with the new decentralized predictor

Usage

forecastfplsr(object, components, h)

Arguments

object	An object of class fts.
components	Number of optimal components.
h	Forecast horizon.

Value

A fts class object, containing forecasts of responses.

Author(s)

Han Lin Shang

References

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

forecast.ftsm, ftsm, plot.fm, plot.ftsf, residuals.fm, summary.fm

Examples

# A set of functions are decomposed by functional partial least squares decomposition.	
# By forecasting univariate partial least squares scores, the forecasted curves are 
# obtained by multiplying the forecasted scores by fixed functional partial least 
# squares function plus fixed mean function.
forecastfplsr(object = ElNino_ERSST_region_1and2, components = 2, h = 5)

ftsa documentation built on Sept. 11, 2023, 5:09 p.m.