tetools function

Temporal reconciliation tools

Some useful tools for forecast reconciliation through temporal hierarchies.

tetools(agg_order, fh = 1, tew = "sum", sparse = TRUE)

Arguments

• 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 $m$.
• fh: Forecast horizon for the lowest frequency (most temporally aggregated) time series (default is 1).
• 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).
• sparse: Option to return sparse matrices (default is TRUE).

Returns

A list with five elements: - dim: A vector containing information about the maximum aggregation order (m), the number of factor (p), the partial (ks) and total sum (kt) of factors.

• set: The vector of the temporal aggregation orders (in decreasing order).

• agg_mat: The temporal linear combination or aggregation matrix.

• strc_mat: The temporal structural matrix.

• cons_mat: The temporal zero constraints matrix.

Examples

# Temporal framework (quarterly data)
obj <- tetools(agg_order = 4, sparse = FALSE)

See Also

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

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