run_grid_search

Run grid search for parameter optimization (parallel PSOCK)

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

run_grid_search function

<dl><dt>path_cpi</dt>
<dd>Path to CPI Excel file</dd>
<dt>path_weights</dt>
<dd>Path to weights Excel file</dd>
<dt>grid_df</dt>
<dd>Data frame with parameter combinations (one row = one config)</dd>
<dt>n_cores</dt>
<dd>Number of cores for parallel processing</dd></dl>

Arguments

Run grid search for parameter optimization (parallel PSOCK) — run_grid_search

<dl>

<dt>path_cpi</dt>
<dd>Path to CPI Excel file</dd>


<dt>path_weights</dt>
<dd>Path to weights Excel file</dd>


<dt>grid_df</dt>
<dd>Data frame with parameter combinations (one row = one config)</dd>


<dt>n_cores</dt>
<dd>Number of cores for parallel processing</dd>

</dl>

run_grid_search: Run grid search for parameter optimization (parallel PSOCK)

Description

Usage

Value

Arguments