TimeSeriesAnalysis
Decomposition
decompose a time series into level, residuals, and potentially trend and seasonal components
Calling Sequence
Parameters
Description
Examples
References
Compatibility
Decomposition(model, ts, extraparameters)
model
-
Exponential smoothing model
ts
Time series consisting of a single data set
extraparameters
(optional) table of parameter values
The Decomposition command takes a time series and decomposes it according to an exponential smoothing model.
It returns a time series with two, three, or four data sets in it: one for the level, one for the residuals, if the model has a trend component then one data set for the trends, and if the model has a seasonal component then a data set for the seasonal component.
Consider the following time series. It represents international tourist visitor nights in Australia.
Fit an exponential smoothing model to it.
Create the decomposition. Since this is a model with both trend and seasonal components, you get four data sets.
Since the error and seasonal components are multiplicative, it makes sense to display them together. The trend and level components are displayed separately.
Hyndman, R.J. and Athanasopoulos, G. (2013) Forecasting: principles and practice. http://otexts.org/fpp/. Accessed on 2013-10-09.
Hyndman, R.J., Koehler, A.B., Ord, J.K., and Snyder, R.D. (2008) Forecasting with Exponential Smoothing: The State Space Approach. Springer Series in Statistics. Springer-Verlag Berlin Heidelberg.
The TimeSeriesAnalysis[Decomposition] command was introduced in Maple 18.
For more information on Maple 18 changes, see Updates in Maple 18.
See Also
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