Joint block bootstrap for generating probabilistic base forecasts that take into account the correlation between different time series (Panagiotelis et al. 2023).
boot_cs(fit, boot_size, h, seed = NULL)A list with two elements: the seed used to sample the errors and a 3-d array (boot\_size n h)
A list of n base forecast models. It is important to note that the models
must have the simulate() function available and implemented as with
the package forecast, with the following mandatory parameters:
object, innov, future, and nsim.
The number of bootstrap replicates.
Block size of the bootstrap, which is typically equivalent to the forecast horizon.
An integer seed.
Panagiotelis, A., Gamakumara, P., Athanasopoulos, G. & Hyndman, R. J. (2023), Probabilistic forecast reconciliation: Properties, evaluation and score optimisation, European Journal of Operational Research 306(2), 693–706.
Other bootstrap:
boot_ct(),
boot_te()