ctf_tools: Cross-temporal reconciliation tools

Description

Some useful tools for the cross-temporal forecast reconciliation of cross-sectionally and temporally constrained time series

Usage

ctf_tools(C, m, h = 1, Ut, nb, Sstruc = FALSE)

Arguments

(na x nb) cross-sectional (contemporaneous) matrix mapping the bottom level series into the higher level ones.

Highest available sampling frequency per seasonal cycle (max. order of temporal aggregation).

Forecast horizon for the lowest frequency (most temporally aggregated) time series (default is 1).

Zero constraints cross-sectional (contemporaneous) kernel matrix \((\textbf{U}'\textbf{Y} = \mathbf{0})\) spanning the null space valid for the reconciled forecasts. It can be used instead of parameter C, but in this case nb (n = na + nb) is needed. If the hierarchy admits a structural representation, Ut has dimension (na x n).

Number of bottom time series; if C is present, nb is not used.

Sstruc

If Sstruc = TRUE the function returns also the structural representation matrix of a cross-temporal system (default is FALSE).

Value

ctf list with:

Ht

Full row-rank cross-temporal zero-valued constraints (kernel) matrix\(,\; \textbf{H}'\textbf{y} = \mathbf{0}\).

Htbreve

Complete, not full row-rank cross-temporal zero-valued constraints (kernel) matrix.

Htstruc

Zero constraints full row-rank cross-temporal kernel matrix (structural representation) \(,\; \check{\textbf{H}}'\).

Sstruc

Cross-temporal summing matrix (structural representation)\(,\; \check{\textbf{S}}\).

hts list from hts_tools

thf list from thf_tools

Examples

Run this code

# NOT RUN {
# One level hierarchy (na = 1, nb = 2) with quarterly data
obj <- ctf_tools(C = matrix(c(1, 1), 1), m = 4, Sstruc = TRUE)
# }

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