BayesianDisaggregation
Bayesian Methods for Economic Data Disaggregation
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.
README
# Example Data Files for BayesianDisaggregation This directory contains example data files for testing and demonstration: ## CPI.xlsx - Annual Consumer Price Index data (2019-2023) - Contains aggregate index (Total) and component indices - Categories: Food, Housing, Transport, Healthcare, Education, Recreation, Other - Base year: 2019 (index = 100) ## WEIGHTS.xlsx - Industry weights matrix for CPI components - Rows: Industries/Categories - Columns: Years (2019-2023) - Each year's weights sum to 1.0 - Format: Industry | 2019 | 2020 | 2021 | 2022 | 2023 These are minimal example files for package testing and documentation. For real analysis, users should provide their own data files with appropriate structure.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.2 |
2026-04-09 windows/windows R-4.5 | BayesianDisaggregation_0.1.2.zip |
158.4 KiB |