boot_te: Temporal Joint Bootstrap

View source: R/bootstrap.R

boot_teR Documentation

Temporal Joint Bootstrap

Description

Joint block bootstrap for generating probabilistic base forecasts that take into account the correlation between different temporal aggregation order (Girolimetto et al. 2023).

Usage

boot_te(fit, boot_size, m, h = 1, seed = NULL)

Arguments

fit

A list of \mjseqn(k^\ast+m) base forecast models ordered as [lowest_freq' ... highest_freq']'. 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.

m

Highest available sampling frequency per seasonal cycle (max. order of temporal aggregation, \mjseqnm), or a subset of \mjseqnp factors of \mjseqnm.

h

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 (\mjseqnboot\_size\times h(k^\ast+m)) matrix

References

Girolimetto, D., Athanasopoulos, G., Di Fonzo, T., & Hyndman, R. J. (2023), Cross-temporal Probabilistic Forecast Reconciliation, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.48550/arXiv.2303.17277")}.

See Also

Other bootstrap: boot_cs(), boot_ct()


FoReco documentation built on May 31, 2023, 5:17 p.m.