Convergence and Dynamic Factor Models

[Up] [Top]

Documentation for package ‘convergenceDFM’ version 0.3.2

Help Pages

build_cluster_map Build a fallback sector-to-cluster map
choose_var_lag Select optimal VAR lag order with multiple criteria
compute_wedge Construct the transformation wedge W = Phi - V = K * G' - p
deltaR2_ou Incremental R-squared from X in OU model
diagnose_data Diagnose and prepare data matrices
estimate_DFM Estimate Dynamic Factor Model with VAR dynamics
estimate_factor_OU Estimate Factor Ornstein-Uhlenbeck / AR(1) model (Stan if available)
make_X_innovations Extract X innovations (reduced-form VAR residuals)
placebo_values Aggregate-preserving placebo values (negative controls for gravitation)
plot_error_correction_panel Plot error correction panel
read_cpi Read CPI data from an Excel file
rescue_short_run_channel Rescue short-run channel test
rotation_null_test Null hypothesis test for X->Y factor coupling
row_norm1 Normalize matrix rows to sum to one
run_complete_factor_analysis_robust Complete factor-OU convergence analysis pipeline
run_convergence_robustness_tests Run comprehensive robustness test suite
run_rotation_null_on_results Run the coupling null test on complete analysis results
select_optimal_components_safe Select optimal number of PLS components with cross-validation
test_cointegration_control Classical cointegration control (Johansen trace or eigen)
test_jackknife_sectors Delete-one-sector jackknife of the X->Y coupling
test_leave_cluster_out Leave-cluster-out robustness of the X->Y coupling
test_permutation_robustness Permutation-based robustness test for X->Y coupling
test_reweighting_robustness Reweighting-based robustness test
to_num_commas Convert localized number strings to numeric
visualize_factor_dynamics Visualize factor dynamics comprehensively
visualize_factor_dynamics_simple Simple factor dynamics visualization
wedge_stationarity Per-sector and panel stationarity / mean-reversion of the wedge