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forecastfplsr

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

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

Functional Time Series Analysis

v6.0
GPL-3
Authors
Rob Hyndman [aut] (<https://orcid.org/0000-0002-2140-5352>), Han Lin Shang [aut, cre, cph] (<https://orcid.org/0000-0003-1769-6430>)
Initial release
2020-11-29

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