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Some useful tools for forecast reconciliation through temporal hierarchies.
thf_tools(m, h = 1, sparse = TRUE)
A list of seven elements:
K
Temporal aggregation matrix.
R
Temporal summing matrix.
Zt
Zero constraints temporal kernel matrix, Z_h'Y' = 0_[hk^* n ].
kset
Set of factors (p) of m in descending order (from m to 1), K = k_p, k_p-1, ..., k_2, k_1, k_p=m, k_1=1.
m
Highest available sampling frequency per seasonal cycle (max. order of temporal aggregation).
p
Number of elements of kset, K.
ks
Sum of p-1 factors of m (out of m itself), k^*.
kt
Sum of all factors of m, k^tot = k^*+m.
Highest available sampling frequency per seasonal cycle (max. order of temporal aggregation, m), or a subset of the p factors of m.
Forecast horizon for the lowest frequency (most temporally aggregated) time series (default is 1).
Option to return sparse object (default is TRUE).
TRUE
Other utilities: Cmatrix(), FoReco2ts(), agg_ts(), arrange_hres(), commat(), ctf_tools(), hts_tools(), lcmat(), oct_bounds(), residuals_matrix(), score_index(), shrink_estim()
Cmatrix()
FoReco2ts()
agg_ts()
arrange_hres()
commat()
ctf_tools()
hts_tools()
lcmat()
oct_bounds()
residuals_matrix()
score_index()
shrink_estim()
# quarterly data obj <- thf_tools(m = 4, sparse = FALSE)
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