This function computes the projection or the mapping matrix \(\mathbf{M}\) and \(\mathbf{G}\), respectively, such that \(\widetilde{\mathbf{y}} = \mathbf{M}\widehat{\mathbf{y}} = \mathbf{S}_{te}\mathbf{G}\widehat{\mathbf{y}}\), where \(\widetilde{\mathbf{y}}\) is the vector of the reconciled forecasts, \(\widehat{\mathbf{y}}\) is the vector of the base forecasts, \(\mathbf{S}_{te}\) is the temporal structural matrix, and \(\mathbf{M} = \mathbf{S}_{te}\mathbf{G}\). For further information regarding on the structure of these matrices, refer to Girolimetto et al. (2023).
teprojmat(agg_order, comb = "ols", res = NULL, mat = "M", tew = "sum", ...)
The projection matrix \(\mathbf{M}\) (mat = "M"
) or
the mapping matrix \(\mathbf{G}\) (mat = "G"
).
Highest available sampling frequency per seasonal cycle (max. order of temporal aggregation, \(m\)), or a vector representing a subset of \(p\) factors of \(m\).
A string specifying the reconciliation method. For a complete list, see tecov.
A (\(N(k^\ast+m) \times 1\)) optional numeric vector containing the in-sample residuals at all the temporal frequencies ordered from the lowest frequency to the highest frequency. This vector is used to compute come covariance matrices.
A string specifying which matrix to return:
"M
" (default) for \(\mathbf{M}\) and "G
" for \(\mathbf{G}\).
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).
Arguments passed on to tecov
mse
If TRUE
(default) the residuals used to compute the covariance
matrix are not mean-corrected.
shrink_fun
Shrinkage function of the covariance matrix, shrink_estim (default)
Girolimetto, D., Athanasopoulos, G., Di Fonzo, T. and Hyndman, R.J. (2024), Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues. International Journal of Forecasting, 40, 3, 1134-1151. tools:::Rd_expr_doi("10.1016/j.ijforecast.2023.10.003")
Utilities:
FoReco2matrix()
,
aggts()
,
balance_hierarchy()
,
commat()
,
csprojmat()
,
cstools()
,
ctprojmat()
,
cttools()
,
df2aggmat()
,
lcmat()
,
recoinfo()
,
res2matrix()
,
shrink_estim()
,
tetools()
,
unbalance_hierarchy()
# Temporal framework (annual-quarterly)
Mte <- teprojmat(agg_order = 4, comb = "ols")
Gte <- teprojmat(agg_order = 4, comb = "ols", mat = "G")
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