Seasonal Trend Decomposition Using Regression
Automatic STR decomposition for time series data
Extract STR components
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Automatic STR decomposition with heuristic search of the parameters
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Plots the results of decomposition
Plots the varying beta coefficients of decomposition
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Objects exported from other packages
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Robust STR decomposition
Seasonal adjustment based on STR
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Automatic STR decomposition
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STR decomposition
Methods for decomposing seasonal data: STR (a Seasonal-Trend time series decomposition procedure based on Regression) and Robust STR. In some ways, STR is similar to Ridge Regression and Robust STR can be related to LASSO. They allow for multiple seasonal components, multiple linear covariates with constant, flexible and seasonal influence. Seasonal patterns (for both seasonal components and seasonal covariates) can be fractional and flexible over time; moreover they can be either strictly periodic or have a more complex topology. The methods provide confidence intervals for the estimated components. The methods can also be used for forecasting.
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