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.
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.
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).
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)