Forecast functional time series
The decentralized response is forecasted by multiplying the estimated regression coefficient with the new decentralized predictor
forecastfplsr(object, components, h)
object |
An object of class |
components |
Number of optimal components. |
h |
Forecast horizon. |
A fts
class object, containing forecasts of responses.
Han Lin Shang
R. J. Hyndman and H. L. Shang (2009) "Forecasting functional time series" (with discussion), Journal of the Korean Statistical Society, 38(3), 199-221.
# 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)
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