FPE                     Final Prediction Error Criterion
HQ                      Hannan-Quinn Criterion
VARtoVMA                Convert VAR to VMA(infinite)
VHARtoVMA               Convert VHAR to VMA(infinite)
alpl                    Evaluate the Density Forecast Based on Average
                        Log Predictive Likelihood (APLP)
autoplot.bvhardynsp     Dynamic Spillover Indices Plot
autoplot.bvharirf       Plot Impulse Responses
autoplot.bvharsp        Plot the Result of BVAR and BVHAR MCMC
autoplot.normaliw       Residual Plot for Minnesota Prior VAR Model
autoplot.predbvhar      Plot Forecast Result
autoplot.summary.bvharsp
                        Plot the Heatmap of SSVS Coefficients
autoplot.summary.normaliw
                        Density Plot for Minnesota Prior VAR Model
bound_bvhar             Setting Empirical Bayes Optimization Bounds
bvar_flat               Fitting Bayesian VAR(p) of Flat Prior
bvar_minnesota          Fitting Bayesian VAR(p) of Minnesota Prior
bvhar_minnesota         Fitting Bayesian VHAR of Minnesota Prior
choose_bayes            Finding the Set of Hyperparameters of Bayesian
                        Model
choose_bvar             Finding the Set of Hyperparameters of
                        Individual Bayesian Model
choose_var              Choose the Best VAR based on Information
                        Criteria
coef                    Coefficient Matrix of Multivariate Time Series
                        Models
compute_dic             Deviance Information Criterion of Multivariate
                        Time Series Model
compute_logml           Extracting Log of Marginal Likelihood
conf_fdr                Evaluate the Sparsity Estimation Based on FDR
conf_fnr                Evaluate the Sparsity Estimation Based on FNR
conf_fscore             Evaluate the Sparsity Estimation Based on F1
                        Score
conf_prec               Evaluate the Sparsity Estimation Based on
                        Precision
conf_recall             Evaluate the Sparsity Estimation Based on
                        Recall
confusion               Evaluate the Sparsity Estimation Based on
                        Confusion Matrix
divide_ts               Split a Time Series Dataset into Train-Test Set
dynamic_spillover       Dynamic Spillover
etf_vix                 CBOE ETF Volatility Index Dataset
fitted                  Fitted Matrix from Multivariate Time Series
                        Models
forecast_expand         Out-of-sample Forecasting based on Expanding
                        Window
forecast_roll           Out-of-sample Forecasting based on Rolling
                        Window
fromse                  Evaluate the Estimation Based on Frobenius Norm
geom_eval               Adding Test Data Layer
gg_loss                 Compare Lists of Models
irf.varlse              Impulse Response Analysis
is.stable               Stability of the process
mae                     Evaluate the Model Based on MAE (Mean Absolute
                        Error)
mape                    Evaluate the Model Based on MAPE (Mean Absolute
                        Percentage Error)
mase                    Evaluate the Model Based on MASE (Mean Absolute
                        Scaled Error)
mrae                    Evaluate the Model Based on MRAE (Mean Relative
                        Absolute Error)
mse                     Evaluate the Model Based on MSE (Mean Square
                        Error)
predict                 Forecasting Multivariate Time Series
print.summary.bvharsp   Summarizing BVAR and BVHAR with Shrinkage
                        Priors
relmae                  Evaluate the Model Based on RelMAE (Relative
                        MAE)
relspne                 Evaluate the Estimation Based on Relative
                        Spectral Norm Error
residuals               Residual Matrix from Multivariate Time Series
                        Models
rmafe                   Evaluate the Model Based on RMAFE
rmape                   Evaluate the Model Based on RMAPE (Relative
                        MAPE)
rmase                   Evaluate the Model Based on RMASE (Relative
                        MASE)
rmsfe                   Evaluate the Model Based on RMSFE
set_bvar                Hyperparameters for Bayesian Models
set_dl                  Dirichlet-Laplace Hyperparameter for
                        Coefficients and Contemporaneous Coefficients
set_factor              Factor Specification
set_gdp                 Generalized Double Pareto Shrinkage
                        Hyperparameters for Coefficients and
                        Contemporaneous Coefficients
set_horseshoe           Horseshoe Prior Specification
set_intercept           Prior for Constant Term
set_lambda              Hyperpriors for Bayesian Models
set_ldlt                Covariance Matrix Prior Specification
set_ng                  Normal-Gamma Hyperparameter for Coefficients
                        and Contemporaneous Coefficients
set_ssvs                Stochastic Search Variable Selection (SSVS)
                        Hyperparameter for Coefficients Matrix and
                        Cholesky Factor
sim_iw                  Generate Inverse-Wishart Random Matrix
sim_matgaussian         Generate Matrix Normal Random Matrix
sim_mncoef              Generate Minnesota BVAR Parameters
sim_mniw                Generate Normal-IW Random Family
sim_mnormal             Generate Multivariate Normal Random Vector
sim_mnvhar_coef         Generate Minnesota BVAR Parameters
sim_mvt                 Generate Multivariate t Random Vector
sim_var                 Generate Multivariate Time Series Process
                        Following VAR(p)
sim_vhar                Generate Multivariate Time Series Process
                        Following VAR(p)
spillover               h-step ahead Normalized Spillover
spne                    Evaluate the Estimation Based on Spectral Norm
                        Error
stableroot              Roots of characteristic polynomial
summary.normaliw        Summarizing Bayesian Multivariate Time Series
                        Model
summary.varlse          Summarizing Vector Autoregressive Model
summary.vharlse         Summarizing Vector HAR Model
var_bayes               Fitting Bayesian VAR with Coefficient and
                        Covariance Prior
var_lm                  Fitting Vector Autoregressive Model of Order p
                        Model
vhar_bayes              Fitting Bayesian VHAR with Coefficient and
                        Covariance Prior
vhar_lm                 Fitting Vector Heterogeneous Autoregressive
                        Model
