boot_cs {FoReco}

Cross-sectional Joint Bootstrap

Description

Joint block bootstrap for generating probabilistic base forecasts that take into account the correlation between different time series (Panagiotelis et al. 2023).

Usage

boot_cs(fit, boot_size, h, seed = NULL)

Arguments

fit

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.

boot_size

The number of bootstrap replicates.

h

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 (\(boot\_size\times n \times h\))

References

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.

See Also

Other bootstrap: boot_ct(), boot_te()