cttools | R Documentation |
Some useful tools for the cross-temporal forecast reconciliation of a linearly constrained (e.g., hierarchical/grouped) multiple time series.
cttools(agg_mat, cons_mat, agg_order, tew = "sum", fh = 1, sparse = TRUE)
agg_mat |
A ( |
cons_mat |
A ( |
agg_order |
Highest available sampling frequency per seasonal cycle (max. order
of temporal aggregation, |
tew |
A string specifying the type of temporal aggregation. Options include:
" |
fh |
Forecast horizon for the lowest frequency (most temporally aggregated)
time series (default is |
sparse |
Option to return sparse matrices (default is |
A list with four elements:
dim |
A vector containing information about the number of series for the
complete system ( |
set |
The vector of the temporal aggregation orders (in decreasing order). |
agg_mat |
The cross-temporal aggregation matrix. |
strc_mat |
The cross-temporal structural matrix. |
cons_mat |
The cross-temporal zero constraints matrix. |
Cross-temporal framework:
ctboot()
,
ctbu()
,
ctcov()
,
ctlcc()
,
ctmo()
,
ctrec()
,
cttd()
,
iterec()
,
tcsrec()
Utilities:
FoReco2matrix()
,
aggts()
,
balance_hierarchy()
,
commat()
,
csprojmat()
,
cstools()
,
ctprojmat()
,
df2aggmat()
,
lcmat()
,
recoinfo()
,
res2matrix()
,
shrink_estim()
,
teprojmat()
,
tetools()
,
unbalance_hierarchy()
# Cross-temporal framework
A <- t(c(1,1)) # Aggregation matrix for Z = X + Y
m <- 4 # from quarterly to annual temporal aggregation
cttools(agg_mat = A, agg_order = m)
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