shrink_estim

Shrinkage of the covariance matrix according to Schäfer and Strimmer (2005).

utilities

Classical (bottom-up and top-down), optimal and heuristic combination forecast
point (Di Fonzo and Girolimetto, 2023) <doi:10.1016/j.ijforecast.2021.08.004> and
probabilistic (Girolimetto et al. 2023) <arXiv:2303.17277> reconciliation procedures
for cross-sectional, temporal, and cross-temporal linearly constrained time series.

Daniele Girolimetto

FoReco

Forecast Reconciliation

Tommaso Di Fonzo

shrink_estim function

<dl><dt>x</dt>
<dd>residual matrix</dd>
<dt>minT</dt>
<dd>this param allows to calculate the covariance matrix according
to the original hts formulation (<code>TRUE</code>) or according to the standard
approach (<code>FALSE</code>).</dd></dl>

Arguments

This function is a modified version of the <code>shrink_estim</code>() hidden function of hts.

Author

Shrinkage of the covariance matrix — shrink_estim

<dl>

<dt>x</dt>
<dd>residual matrix</dd>


<dt>minT</dt>
<dd>this param allows to calculate the covariance matrix according
to the original hts formulation (<code>TRUE</code>) or according to the standard
approach (<code>FALSE</code>).</dd>

</dl>

shrink_estim: Shrinkage of the covariance matrix

Description

Usage

Value

Arguments

Author

References

See Also