Decompose a multiple seasonal time series into seasonal, trend and remainder
components. Seasonal components are estimated iteratively using STL. The trend
component is computed for the last iteration of STL. Non-seasonal time series
are decomposed into trend and remainder only. In this case,
is used to estimate the trend.
Optionally, the time series may be Box-Cox transformed before decomposition.
mstl(x, lambda = NULL, iterate = 2, s.window = 21, ...)
Univariate time series of class
Box-Cox decomposition parameter. If
Number of iterations to use to refine the seasonal component.
Seasonal windows to be used in the decompositions. If scalar, the same value is used for all seasonal components. Otherwise, it should be a vector of the same length as the number of seasonal components.
Other arguments are passed to