stlar: STL-AR method
In seer: Feature-Based Forecast Model Selection
stlar R Documentation
STL-AR method
Description
STL decomposition method applied to the time series, then an AR model is used to
forecast seasonally adjusted data, while the seasonal naive method is used to forecast
the seasonal component
Usage
stlar(y, h = 10, s.window = 11, robust = FALSE)
Arguments
y
a univariate time series
h
forecast horizon
s.window
Either the character string “periodic” or the span (in lags) of the loess window for seasonal extraction
robust
logical indicating if robust fitting be used in the loess procedue
Value
return object of class forecast
Author(s)
Thiyanga Talagala
seer documentation built on Oct. 1, 2022, 9:06 a.m.
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| stlar | R Documentation |
STL-AR method
Description
STL decomposition method applied to the time series, then an AR model is used to forecast seasonally adjusted data, while the seasonal naive method is used to forecast the seasonal component
Usage
stlar(y, h = 10, s.window = 11, robust = FALSE)
Arguments
y |
a univariate time series |
h |
forecast horizon |
s.window |
Either the character string “periodic” or the span (in lags) of the loess window for seasonal extraction |
robust |
logical indicating if robust fitting be used in the loess procedue |
Value
return object of class forecast
Author(s)
Thiyanga Talagala
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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