temporal_stability

Rewards smooth posteriors by penalizing average absolute period-to-period
changes per sector. Maps to \([0,1]\) via \(1/(1 + \kappa \cdot \mathrm{mv})\).

Implements a novel Bayesian disaggregation framework that combines
Principal Component Analysis (PCA) and Singular Value Decomposition (SVD)
dimension reduction of prior weight matrices with deterministic Bayesian
updating rules. The method provides Markov Chain Monte Carlo (MCMC) free
posterior estimation with built-in diagnostic metrics. While based on
established PCA (Jolliffe, 2002) <doi:10.1007/b98835> and Bayesian principles
(Gelman et al., 2013) <doi:10.1201/b16018>, the specific integration for
economic disaggregation represents an original methodological contribution.

José Mauricio Gómez Julián

BayesianDisaggregation

Bayesian Methods for Economic Data Disaggregation

temporal_stability function

<dl><dt>W</dt>
<dd>Posterior matrix (\(T \times K\)).</dd>
<dt>kappa</dt>
<dd>Sensitivity to average absolute change (default <code>50</code>).</dd></dl>

Arguments

Temporal stability (smoothness over time) — temporal_stability

<dl>

<dt>W</dt>
<dd>Posterior matrix (\(T \times K\)).</dd>


<dt>kappa</dt>
<dd>Sensitivity to average absolute change (default <code>50</code>).</dd>

</dl>

temporal_stability: Temporal stability (smoothness over time)

Description

Usage

Value

Arguments

Examples