Bayesian Vector Heterogeneous Autoregressive Modeling
Dynamic Spillover Indices Plot
Plot Impulse Responses
Plot the Result of BVAR and BVHAR MCMC
Residual Plot for Minnesota Prior VAR Model
Plot Forecast Result
Plot the Heatmap of SSVS Coefficients
Density Plot for Minnesota Prior VAR Model
Setting Empirical Bayes Optimization Bounds
Fitting Bayesian VAR(p) of Flat Prior
Fitting Bayesian VAR(p) of Horseshoe Prior
Fitting Bayesian VAR(p) of Minnesota Prior
Fitting Bayesian VAR(p) of SSVS Prior
Fitting Bayesian VAR-SV
Fitting Bayesian VHAR of Horseshoe Prior
Fitting Bayesian VHAR of Minnesota Prior
Fitting Bayesian VHAR of SSVS Prior
Fitting Bayesian VHAR-SV
bvhar: Bayesian Vector Heterogeneous Autoregressive Modeling
Finding the Set of Hyperparameters of Bayesian Model
Finding the Set of Hyperparameters of Individual Bayesian Model
Choose the Hyperparameters Set of SSVS-VAR using a Default Semiautomat...
Choose the Best VAR based on Information Criteria
Coefficient Matrix of Multivariate Time Series Models
Deviance Information Criterion of Multivariate Time Series Model
Extracting Log of Marginal Likelihood
Evaluate the Sparsity Estimation Based on FDR
Evaluate the Sparsity Estimation Based on FNR
Evaluate the Sparsity Estimation Based on F1 Score
Evaluate the Sparsity Estimation Based on Precision
Evaluate the Sparsity Estimation Based on Recall
Evaluate the Sparsity Estimation Based on Confusion Matrix
Split a Time Series Dataset into Train-Test Set
Dynamic Spillover
Time points and Financial Events
Fitted Matrix from Multivariate Time Series Models
Out-of-sample Forecasting based on Expanding Window
Out-of-sample Forecasting based on Rolling Window
Final Prediction Error Criterion
Evaluate the Estimation Based on Frobenius Norm
Adding Test Data Layer
Compare Lists of Models
Hannan-Quinn Criterion
Initial Parameters of Stochastic Search Variable Selection (SSVS) Mode...
Impulse Response Analysis
Stability of the process
Evaluate the Model Based on MAE (Mean Absolute Error)
Evaluate the Model Based on MAPE (Mean Absolute Percentage Error)
Evaluate the Model Based on MASE (Mean Absolute Scaled Error)
Evaluate the Model Based on MRAE (Mean Relative Absolute Error)
Evaluate the Model Based on MSE (Mean Square Error)
Pipe operator
Forecasting Multivariate Time Series
Objects exported from other packages
Evaluate the Model Based on RelMAE (Relative MAE)
Evaluate the Estimation Based on Relative Spectral Norm Error
Residual Matrix from Multivariate Time Series Models
Evaluate the Model Based on RMAFE
Evaluate the Model Based on RMAPE (Relative MAPE)
Evaluate the Model Based on RMASE (Relative MASE)
Evaluate the Model Based on RMSFE
Hyperparameters for Bayesian Models
Dirichlet-Laplace Hyperparameter for Coefficients and Contemporaneous ...
Horseshoe Prior Specification
Prior for Constant Term
Hyperpriors for Bayesian Models
Covariance Matrix Prior Specification
Normal-Gamma Hyperparameter for Coefficients and Contemporaneous Coeff...
Stochastic Search Variable Selection (SSVS) Hyperparameter for Coeffic...
Generate Generalized Inverse Gaussian Distribution
Generate Horseshoe Parameters
Generate Inverse-Wishart Random Matrix
Generate Matrix Normal Random Matrix
Generate Minnesota BVAR Parameters
Generate Normal-IW Random Family
Generate Multivariate Normal Random Vector
Generate Minnesota BVAR Parameters
Generate Multivariate t Random Vector
Generate SSVS Parameters
Generate Multivariate Time Series Process Following VAR(p)
Generate Multivariate Time Series Process Following VAR(p)
h-step ahead Normalized Spillover
Evaluate the Estimation Based on Spectral Norm Error
Roots of characteristic polynomial
Summarizing BVAR and BVHAR with Shrinkage Priors
Summarizing Bayesian Multivariate Time Series Model
Summarizing Vector Autoregressive Model
Summarizing Vector HAR Model
Fitting Bayesian VAR with Coefficient and Covariance Prior
Fitting Vector Autoregressive Model of Order p Model
Convert VAR to VMA(infinite)
Fitting Bayesian VHAR with Coefficient and Covariance Prior
Fitting Vector Heterogeneous Autoregressive Model
Convert VHAR to VMA(infinite)
Tools to model and forecast multivariate time series including Bayesian Vector heterogeneous autoregressive (VHAR) model by Kim & Baek (2023) (<doi:10.1080/00949655.2023.2281644>). 'bvhar' can model Vector Autoregressive (VAR), VHAR, Bayesian VAR (BVAR), and Bayesian VHAR (BVHAR) models.
Useful links