VPSPulse Mirrors

High-Performance Open-Source Archive

Introduction to Convergence Analysis with convergenceDFM

Introduction to Convergence Analysis with convergenceDFM

library(convergenceDFM)
#> convergenceDFM 0.1.4 - Dynamic Factor Models for Economic Convergence
#> Type vignette('convergence-analysis') for an introduction

Introduction

The convergenceDFM package provides a comprehensive framework for analyzing economic convergence using Dynamic Factor Models (DFM) and Factor Ornstein-Uhlenbeck processes.

Basic Usage

# Load example data
data("example_marxist_data")

# Run complete analysis
results <- run_complete_factor_analysis_robust(
  X_matrix = marxist_prices[, -1],
  Y_matrix = bayesian_cpi[, -1],
  max_comp = 3,
  dfm_lags = 1,
  ou_chains = 4,
  ou_iter = 2000
)

# View results
summary(results)

Convergence Tests

The package includes several convergence tests:

  1. Formal convergence tests: Unit root tests, cointegration
  2. Robustness tests: Permutation, reweighting, jackknife
  3. Rotation null tests: Testing coupling between factor spaces

Visualization

# Visualize factor dynamics
visualize_factor_dynamics(
  dfm_result = results$dfm,
  ou_result = results$factor_ou,
  factors_data = results$factors
)

Need mirroring services?
Contact our team at info@vpspulse.com.

Mirror powered by VPSpulse

Infrastructure sponsored by VPSPulse & Secure Payments by ArionPay.