FoReco (version 1.2.0)

as_tevector: Convert between horizon-stacked and temporal layouts

Description

These functions convert matrix between the two canonical layouts used in temporal reconciliation. Let \(m\) be the maximum temporal aggregation order and \(k^\ast\) the sum of a subset of the \((p-1)\) proper factors of \(m\) (excluding \(m\)); let \(h\) be the forecast horizon for the lowest frequency series (e.g., most aggregated temporal forecast horizon):

• Horizon-stacked layout (temporal version): a \(h \times (k^\ast + m)\) matrix where rows are the most aggregated temporal forecast horizons, and the values in each row are ordered from the lowest frequency (most temporally aggregated) to the highest frequency.

• Temporal layout: a (\(h(k^\ast + m) \times 1\)) numeric vector where values are ordered from the lowest frequency (most temporally aggregated) to the highest frequency.

Then, as_tevector converts a \((h \times (k^\ast+m))\) horizon-stacked matrix to a (\(h(k^\ast + m) \times 1\)) temporal vector; as_hstack_telayout performs the inverse transform.

Usage

as_tevector(hmat, agg_order)
as_hstack_telayout(tevec, agg_order)

Value

as_tevector returns a (\(h(k^\ast + m) \times 1\)) numeric vector in temporal layout.

as_hstack_telayout returns a \(h \times (k^\ast+m)\) numeric matrix in horizon-stacked layout (temporal version).

Arguments

hmat

A \(h \times (k^\ast+m)\) numeric matrix in horizon-stacked layout (temporal version).

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 \(m\).

tevec

A (\(h(k^\ast + m) \times 1\)) numeric vector in temporal layout.

See Also

Utilities: FoReco2matrix(), aggts(), as_ctmatrix(), balance_hierarchy(), commat(), csprojmat(), cstools(), ctprojmat(), cttools(), df2aggmat(), lcmat(), recoinfo(), res2matrix(), set_bounds(), shrink_estim(), shrink_oasd(), teprojmat(), tetools(), unbalance_hierarchy()

Examples

h <- 2   # horizons
m <- 4   # temporal aggregation order
kt <- tetools(m)$dim["kt"]

# Build a horizon-stacked matrix: h rows, n * k_t columns
input_te <- seq_len(h * kt)

hmat <- as_hstack_telayout(input_te, agg_order = m)
tevec <- as_tevector(hmat, agg_order = m)
# all.equal(tevec, input_te, check.attributes = FALSE)