Package index • tsbs

All functions

adcc_bootstrap_se(): Bootstrap Standard Errors for ADCC Parameters
adcc_comprehensive_inference(): Comprehensive ADCC Inference
adcc_copula_nll(): ADCC Copula Negative Log-Likelihood
adcc_standard_errors(): Compute Standard Errors for ADCC Parameters
analyze_iteration(): Analyze Iteration in Detail
as.data.frame(<tsbs_diagnostics>): Convert Diagnostics to Data Frame
benchmark_tsbs(): Benchmark Bootstrap Methods
blockBootstrap(): Block Bootstrap for Time Series (Rcpp Implementation)
blockBootstrap_with_diagnostics(): Block Bootstrap with Diagnostics
bootstrap_diagnostics: Bootstrap Diagnostics System for tsbs Package
calculate_loglik_vector_r(): Calculate the Log-Likelihood Vector (R Helper)
cgarch_bootstrap_se(): Bootstrap Standard Errors for CGARCH Parameters
cgarch_standard_errors(): Compute Standard Errors for CGARCH Models
check_all_states_constant(): Check for All-States-Constant Event
check_cgarch_problems(): Check CGARCH-Specific Problems
check_convergence(): Check Convergence Achievement
check_em_monotonicity(): Check EM Monotonicity
check_gogarch_problems(): Check GOGARCH-Specific Problems
check_param_stationarity(): Check Parameter Stationarity
check_sigma_updates(): Check for Sigma Update Failures
compare_states(): Compare States
compute_adcc_standard_errors_robust(): Compute ADCC Standard Errors with Robust Edge Case Handling
compute_bootstrap_diagnostics(): Compute Diagnostics from Bootstrap Series
compute_cgarch_nll_surface(): Compute NLL Surface for CGARCH(1,1)
compute_cgarch_residuals(): Compute Copula Residuals from Simulated CGARCH Data
compute_cgarch_standard_errors_robust(): Robust CGARCH Standard Errors with Edge Case Handling
compute_dcc_standard_errors_robust(): Compute DCC Standard Errors with Robust Edge Case Handling
compute_func_out_cv(): Compute Coefficient of Variation for Bootstrap Outputs
compute_gogarch_standard_errors_robust(): Robust GOGARCH Standard Errors with Edge Case Handling
compute_loglik_fixed(): Compute Log-Likelihood with Fixed Parameters
compute_nll_surface(): Compute NLL Surface for DCC(1,1)
compute_robust_estimates(): Compute Robust Estimates from Bootstrap Outputs
compute_std_residuals(): Compute Standardized Residuals from Simulated DCC-GARCH Data
copula_nll(): Copula Negative Log-Likelihood for DCC(1,1)
correlation_bootstrap_se(): Bootstrap Standard Errors for Correlation Parameters
correlation_comprehensive_inference(): Comprehensive Correlation Model Inference
correlation_profile_likelihood_ci(): Profile Likelihood Confidence Intervals
create_garch_spec_object_r(): Create a GARCH Specification Object (Convenience Function)
create_test_dcc_spec(): Create a standard DCC spec for testing
dcc11_bootstrap_se(): Bootstrap Standard Errors for DCC(1,1) Parameters
dcc11_confint(): Compute Confidence Intervals for DCC(1,1) Parameters
dcc11_estimation_summary(): Summarize DCC(1,1) Estimation Results
dcc11_gradient(): Full DCC(1,1) Gradient Function for Optimizer
dcc11_hessian(): Compute DCC(1,1) Hessian with Full Diagnostics
dcc11_nll(): DCC(1,1) Weighted Negative Log-Likelihood
dcc11_observed_information(): Compute Observed Information Matrix for DCC(1,1)
dcc11_profile_ci(): Compute Profile Likelihood Confidence Intervals
dcc11_sandwich_se(): Compute Sandwich (Robust) Standard Errors
dcc11_standard_errors(): Compute Standard Errors for DCC(1,1) Parameters
dcc11_transform_se(): Transform Standard Errors Between Parameterizations
default_model_func(): Default Model Fitting Function
diagnostic_summary_stats(): Get Diagnostic Summary Statistics
diagnostic_utils: Diagnostic Utility Functions for MS-VARMA-GARCH
.check_expression_validity(): Check if expression or variable exists and is evaluable
.estimate_p(): Estimate geometric distribution parameter p for stationary bootstrap
.is_invalid_count(): Invalid input count
.is_invalid_data(): Invalid input data
.not_in_unit_interval(): Value not in unit interval
estimate_adcc_copula(): Estimate ADCC Copula Parameters
estimate_arma_weighted_r(): Estimate Conditional Mean Parameters (R Helper)
estimate_garch_weighted_r(): Estimate GARCH Parameters for Multivariate Models (R Helper)
estimate_gogarch_improved(): Estimate GOGARCH with Improved ICA
etf_prices: ETF Portfolio Price Data
etf_returns: ETF Portfolio Returns Data
evaluate_ica_quality(): Evaluate ICA Quality
export_diagnostics_csv(): Export Diagnostics to CSV Files
extract_blocks(): Extract Block Information from Diagnostics
extract_cgarch_trajectory(): Extract CGARCH Parameter Trajectory
extract_cgarch_trajectory_with_ll(): Extract CGARCH Trajectory with Log-Likelihood
extract_dcc_trajectory(): Extract DCC Parameter Trajectory from MS Diagnostics
extract_dcc_trajectory_with_ll(): Extract DCC Trajectory with Log-Likelihood
extract_func_out_matrix(): Extract Bootstrap Output Matrix
extract_gogarch_trajectory(): Extract GOGARCH Parameter Trajectory
extract_ll_trajectory(): Extract Log-Likelihood Trajectory
extract_param_trajectory(): Extract Parameter Trajectory
extract_sigma_stats(): Extract Sigma Evolution Statistics
extract_summary_stats(): Extract Summary Statistics from Diagnostics
fit_ms_varma_garch(): Fit a Flexible N-State Markov-Switching Vector-ARMA-GARCH Model
fit_ms_varma_garch_cpp(): Fit a general MS-ARMA-GARCH model via the EM Algorithm in C++
fit_msvar(): Fit a 2-State Markov-Switching Vector Autoregressive Model (MS-VAR)
generate_cgarch_spec(): Generate CGARCH Specification
generate_dcc_spec(): Generate Model Specification for DCC-GARCH
generate_gogarch_spec(): Generate GOGARCH Specification
get_demo_path(): Get path to a specific demo Rmd file
gogarch_bootstrap_se(): Bootstrap Standard Errors for GOGARCH Parameters
gogarch_comprehensive_inference(): GOGARCH Comprehensive Inference
gogarch_diagnostics(): GOGARCH Model Diagnostics
gogarch_estimation_summary(): GOGARCH Estimation Summary
gogarch_standard_errors(): Compute Standard Errors for GOGARCH Models
hmm_bootstrap(): Hidden Markov Model (HMM) Bootstrap for Multivariate Time Series
hmm_bootstrap_old(): Hidden Markov Model (HMM) Bootstrap for Multivariate Time Series
identify_problematic_states(): Identify Problematic States
improved_ica_decomposition(): Improved ICA Decomposition for GOGARCH
k_fold_cv_ts(): K-Fold Cross-Validation for Time Series
list_package_demos(): List available demonstration Rmd files
load_diagnostics(): Load Diagnostics from File
mae(): Mean Absolute Error (MAE)
ms_varma_garch_bs(): Stationary Bootstrap for a General MS-VARMA-GARCH Model
mse(): Mean Squared Error (MSE)
msvar_bootstrap(): Stationary Bootstrap for a 2-State MS-VAR(1) Model
open_demo(): Open a demo Rmd file in RStudio or default editor
perform_m_step_parallel_r(): Perform the M-Step in Parallel (R Helper)
perform_m_step_r(): Perform the M-Step (Sequential Execution)
plot(<ms_diagnostics>): Plot Diagnostics for MS-VARMA-GARCH Models
plot(<tsbs_benchmark>): Plot Method for tsbs_benchmark
plot(<tsbs_diagnostics>): Plot Method for Bootstrap Diagnostics
plot_block_coverage(): Plot Block Coverage for Bootstrap Diagnostics
plot_block_lengths(): Plot Block Length Distribution
plot_cgarch_nll_contours(): Plot CGARCH NLL Contours
plot_coverage_diagnostic(): Plot Coverage Diagnostic
plot_mc_estimates(): Plot Monte Carlo Estimate Distribution
plot_mc_estimates_generic(): Plot Monte Carlo Estimates (Generic)
plot_mixing_matrix(): Plot GOGARCH Mixing Matrix Heatmap
plot_nll_contours(): Plot NLL Contours with plotly
plot_nll_surface_3d(): Plot 3D NLL Surface with plotly
plot_optimization_trace(): Plot Parameter Trace from Optimization
plot_regime_composition(): Plot Regime Composition of Bootstrap Series
print(<tsbs_benchmark>): Print Method for tsbs_benchmark
print(<tsbs_diagnostics>): Print Method for Bootstrap Diagnostics
print_cgarch_mc_results(): Print CGARCH Monte Carlo Results
print_gogarch_mc_results(): Print GOGARCH Monte Carlo Results
print_inference_comparison(): Print Inference Comparison
print_mc_results(): Print Monte Carlo Results
run_cgarch_monte_carlo(): Run Monte Carlo Study for CGARCH(1,1) Estimation with ADCC Support
run_complete_cgarch_diagnostics(): Summary Function for Complete CGARCH Diagnostic Analysis
run_complete_diagnostics(): Summary Function for Complete Diagnostic Analysis
run_complete_gogarch_diagnostics(): Complete GOGARCH Diagnostics
run_dcc_monte_carlo(): Run Monte Carlo Study for DCC(1,1) Estimation
run_gogarch_monte_carlo(): Run Monte Carlo Study for GOGARCH Estimation
save_diagnostics(): Export Diagnostics to File
simulate_cgarch(): Simulate CGARCH Data with ADCC Support
simulate_dcc_garch(): Simulate DCC-GARCH Data with Higher-Order Support
simulate_dcc_garch_test_data(): Simulate DCC-GARCH data for testing
simulate_gogarch(): Simulate GOGARCH Data
summarize_func_outs(): Summarize Bootstrap Functional Outputs
summary.ms_diagnostics(): Summarize Diagnostics
summary.tsbs_benchmark(): Summary Method for tsbs_benchmark
summary(<tsbs_diagnostics>): Summary Method for Bootstrap Diagnostics
test_estimate_normality(): Test Normality of Standardized Estimates
test_estimate_normality_generic(): Test Normality of Standardized Estimates (Generic)
tsbs(): Advanced Bootstrap for Time Series
visualize_dcc_evolution(): Visualize DCC Parameter Evolution from EM Fit
visualize_gogarch_evolution(): Visualize GOGARCH Component Evolution
visualize_standalone_optimization(): Quick Visualization of DCC Optimization Path (Standalone)
wild_bootstrap(): Wild Bootstrap for Time Series Residuals