Joint block bootstrap for generating probabilistic base forecasts that take into account the correlation between different time series (Panagiotelis et al. 2023).
Arguments
- model_list
A list of all the \(n\) base forecasts models. A
simulate()function for each model has to be available and implemented according to the package forecast, with the following mandatory parameters: object, innov, future, and nsim.- boot_size
The number of bootstrap replicates.
- block_size
Block size of the bootstrap, which is typically equivalent to the forecast horizon.
- seed
An integer seed.
Value
A list with two elements: the seed used to sample the errors and a 3-d array (\(\text{boot\_size}\times n \times \text{block\_size}\)).
References
Panagiotelis, A., Gamakumara, P., Athanasopoulos, G. and Hyndman, R.J. (2023), Probabilistic forecast reconciliation: Properties, evaluation and score optimisation, European Journal of Operational Research 306(2), 693–706. doi:10.1016/j.ejor.2022.07.040