.get_Au

Constructs the aggregation matrix Au for the sub-hierarchy composed only
of the upper variables. This matrix relates the "upper uppers" to the
"lowest uppers" (the most disaggregated level of the upper hierarchy).

internal

Provides methods for probabilistic reconciliation of hierarchical forecasts of time series.
The available methods include analytical Gaussian reconciliation (Corani et al., 2021)
<doi:10.1007/978-3-030-67664-3_13>,
MCMC reconciliation of count time series (Corani et al., 2024)
<doi:10.1016/j.ijforecast.2023.04.003>,
Bottom-Up Importance Sampling (Zambon et al., 2024)
<doi:10.1007/s11222-023-10343-y>,
methods for the reconciliation of mixed hierarchies (Mix-Cond and TD-cond) (Zambon et al., 2024)
<https://proceedings.mlr.press/v244/zambon24a.html>,
analytical reconciliation with Bayesian treatment of the covariance matrix (Carrara et al., 2025)
<doi: 10.48550/arXiv.2506.19554>.

Dario Azzimonti

bayesRecon

Probabilistic Reconciliation via Conditioning

Lorenzo Zambon

Stefano Damato

Nicolò Rubattu

Giorgio Corani

.get_Au function

<dl><dt>A</dt>
<dd>Aggregation matrix (must be hierarchical)</dd>
<dt>lowest_rows</dt>
<dd>Optional. Integer vector of row indices corresponding to
the lowest upper level. If NULL, computed using <code>.lowest_lev(A)</code>.</dd></dl>

Arguments

Get aggregation matrix of upper sub-hierarchy — .get_Au

<dl>

<dt>A</dt>
<dd>Aggregation matrix (must be hierarchical)</dd>


<dt>lowest_rows</dt>
<dd>Optional. Integer vector of row indices corresponding to
the lowest upper level. If NULL, computed using <code>.lowest_lev(A)</code>.</dd>

</dl>

.get_Au: Get aggregation matrix of upper sub-hierarchy

Description

Usage

Value

Arguments