ctboot {FoReco} | R Documentation |
Cross-temporal joint block bootstrap
Description
Joint block bootstrap for generating probabilistic base forecasts that take into account the correlation between variables at different temporal aggregation orders (Girolimetto et al. 2023).
Usage
ctboot(model_list, boot_size, agg_order, block_size = 1, seed = NULL)
Arguments
model_list |
A list of |
boot_size |
The number of bootstrap replicates. |
agg_order |
Highest available sampling frequency per seasonal cycle (max. order
of temporal aggregation, |
block_size |
Block size of the bootstrap, which is typically equivalent to the forecast horizon for the most temporally aggregated series. |
seed |
An integer seed. |
Value
A list with two elements: the seed used to sample the errors and
a (\text{boot\_size}\times n(k^\ast+m)\text{block\_size}
) matrix.
References
Girolimetto, D., Athanasopoulos, G., Di Fonzo, T. and Hyndman, R.J. (2023), Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues. International Journal of Forecasting, 40(3), 1134-1151. doi:10.1016/j.ijforecast.2023.10.003
See Also
Bootstrap samples:
csboot()
,
teboot()
Cross-temporal framework:
ctbu()
,
ctcov()
,
ctlcc()
,
ctmo()
,
ctrec()
,
cttd()
,
cttools()
,
iterec()
,
tcsrec()