FoReco (version 1.0.0)

tetd: Temporal top-down reconciliation

Description

Top-down forecast reconciliation for a univariate time series, where the forecast of the most aggregated temporal level is disaggregated according to a proportional scheme (weights). Besides fulfilling any aggregation constraint, the top-down reconciled forecasts should respect two main properties:

• the top-level value remains unchanged;

• all the bottom time series reconciled forecasts are non-negative.

Usage

tetd(base, agg_order, weights, tew = "sum", normalize = TRUE)

Value

A (\(h(k^\ast+m) \times 1\)) numeric vector of temporal reconciled forecasts.

Arguments

base

A (\(hm \times 1\)) numeric vector containing the temporal aggregated base forecasts of order \(m\); \(m\) is the max aggregation order, and \(h\) is the forecast horizon for the lowest frequency time series.

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 \(m\).

weights

A (\(hm \times 1\)) numeric vector containing the proportions for the high-frequency time series; \(m\) is the max aggregation order, and \(h\) is the forecast horizon for the lowest frequency time series.

tew

A string specifying the type of temporal aggregation. Options include: "sum" (simple summation, default), "avg" (average), "first" (first value of the period), and "last" (last value of the period).

normalize

If TRUE (default), the weights will sum to 1.

See Also

Top-down reconciliation: cstd(), cttd()

Temporal framework: teboot(), tebu(), tecov(), telcc(), temo(), terec(), tetools()

Examples

set.seed(123)
# (2 x 1) top base forecasts vector (simulated), forecast horizon = 2
topf <- rnorm(2, 10)
# Same weights for different forecast horizons
fix_weights <- runif(4)
reco <- tetd(base = topf, agg_order = 4, weights = fix_weights)

# Different weights for different forecast horizons
h_weights <- runif(4*2)
recoh <- tetd(base = topf, agg_order = 4, weights = h_weights)