ctboot: Cross-temporal joint block bootstrap

In FoReco: Forecast Reconciliation

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 n elements, one for each cross-sectional series. Each elements is a list with the (k^\ast+m) base forecasts models ordered from the lowest frequency (most temporally aggregated) to the highest frequency. 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.
agg_order	Highest available sampling frequency per seasonal cycle (max. order of temporal aggregation, m), or a vector representing a subset of p factors of m.
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, in press. \Sexpr[results=rd]{tools:::Rd_expr_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()

FoReco documentation built on Sept. 14, 2024, 9:07 a.m.