bld.mbb.bootstrap: Box-Cox and Loess-based decomposition bootstrap.
Description
Generates bootstrapped versions of a time series using the Box-Cox and
Loess-based decomposition bootstrap.
Usage
bld.mbb.bootstrap(x, num, block_size = NULL)
Arguments
x
Original time series.
num
Number of bootstrapped versions to generate.
block_size
Block size for the moving block bootstrap.
Value
A list with bootstrapped versions of the series. The first series in
the list is the original series.
Details
The procedure is described in Bergmeir et al. Box-Cox decomposition is
applied, together with STL or Loess (for non-seasonal time series), and the
remainder is bootstrapped using a moving block bootstrap.
References
Bergmeir, C., R. J. Hyndman, and J. M. Benitez (2016). Bagging
Exponential Smoothing Methods using STL Decomposition and Box-Cox
Transformation. International Journal of Forecasting 32, 303-312.