Some useful tools for forecast reconciliation through temporal hierarchies.
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).
Value
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.
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()