# Bayesian Vector Heterogeneous Autoregressive Modeling

## Documentation for package ‘bvhar’ version 1.0.0

- DESCRIPTION file.
- Package NEWS.

## Help Pages

A B C D E F G H I K L M O P R S V

## -- A --

AIC.bvarflat | Akaike's Information Criterion of Multivariate Time Series Model
AIC.bvarmn | Akaike's Information Criterion of Multivariate Time Series Model
AIC.bvharmn | Akaike's Information Criterion of Multivariate Time Series Model
AIC.varlse | Akaike's Information Criterion of Multivariate Time Series Model
AIC.vharlse | Akaike's Information Criterion of Multivariate Time Series Model
analyze_ir | Impulse Response Analysis
analyze_ir.varlse | Impulse Response Analysis
analyze_ir.vharlse | Impulse Response Analysis
autolayer.predbvhar | Plot Forecast Result
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

## -- B --

BIC.bvarflat | Bayesian Information Criterion of Multivariate Time Series Model
BIC.bvarmn | Bayesian Information Criterion of Multivariate Time Series Model
BIC.bvharmn | Bayesian Information Criterion of Multivariate Time Series Model
BIC.varlse | Bayesian Information Criterion of Multivariate Time Series Model
BIC.vharlse | Bayesian Information Criterion of Multivariate Time Series 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
bvar_niwhm | Fitting Hierarchical Bayesian VAR(p)
bvar_ssvs | Fitting Bayesian VAR(p) of SSVS Prior
bvar_sv | Fitting Bayesian VAR-SV of Minnesota Belief
bvhar_minnesota | Fitting Bayesian VHAR of Minnesota Prior
bvhar_ssvs | Fitting Bayesian VHAR of SSVS Prior
bvhar_sv | Fitting Bayesian VHAR-SV of Minnesota Belief

## -- C --

choose_bayes | Finding the Set of Hyperparameters of Bayesian Model
choose_bvar | Finding the Set of Hyperparameters of Individual Bayesian Model
choose_bvhar | Finding the Set of Hyperparameters of Individual Bayesian Model
choose_ssvs | Choose the Hyperparameters Set of SSVS-VAR using a Default Semiautomatic Approach
choose_var | Choose the Best VAR based on Information Criteria
coef.bvarflat | Coefficient Matrix of Multivariate Time Series Models
coef.bvarmn | Coefficient Matrix of Multivariate Time Series Models
coef.bvharmn | Coefficient Matrix of Multivariate Time Series Models
coef.bvharsp | Coefficient Matrix of Multivariate Time Series Models
coef.summary.bvharsp | Coefficient Matrix of Multivariate Time Series Models
coef.varlse | Coefficient Matrix of Multivariate Time Series Models
coef.vharlse | Coefficient Matrix of Multivariate Time Series Models
compute_dic | Deviance Information Criterion of Multivariate Time Series Model
compute_dic.bvarmn | Deviance Information Criterion of Multivariate Time Series Model
compute_logml | Extracting Log of Marginal Likelihood
compute_logml.bvarmn | Extracting Log of Marginal Likelihood
compute_logml.bvharmn | Extracting Log of Marginal Likelihood
confusion | Evaluate the Sparsity Estimation Based on Confusion Matrix
confusion.summary.bvharsp | Evaluate the Sparsity Estimation Based on Confusion Matrix
conf_fdr | Evaluate the Sparsity Estimation Based on FDR
conf_fdr.summary.bvharsp | Evaluate the Sparsity Estimation Based on FDR
conf_fnr | Evaluate the Sparsity Estimation Based on FNR
conf_fnr.summary.bvharsp | Evaluate the Sparsity Estimation Based on FNR
conf_fscore | Evaluate the Sparsity Estimation Based on F1 Score
conf_fscore.summary.bvharsp | Evaluate the Sparsity Estimation Based on F1 Score
conf_prec | Evaluate the Sparsity Estimation Based on Precision
conf_prec.summary.bvharsp | Evaluate the Sparsity Estimation Based on Precision
conf_recall | Evaluate the Sparsity Estimation Based on Recall
conf_recall.summary.bvharsp | Evaluate the Sparsity Estimation Based on Recall

## -- D --

divide_ts | Split a Time Series Dataset into Train-Test Set

## -- E --

etf_vix | CBOE ETF Volatility Index Dataset

## -- F --

fitted.bvarflat | Fitted Matrix from Multivariate Time Series Models
fitted.bvarmn | Fitted Matrix from Multivariate Time Series Models
fitted.bvharmn | Fitted Matrix from Multivariate Time Series Models
fitted.varlse | Fitted Matrix from Multivariate Time Series Models
fitted.vharlse | 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
FPE | Final Prediction Error Criterion
FPE.varlse | Final Prediction Error Criterion of Multivariate Time Series Model
FPE.vharlse | Final Prediction Error Criterion of Multivariate Time Series Model
fromse | Evaluate the Estimation Based on Frobenius Norm
fromse.bvharsp | Evaluate the Estimation Based on Frobenius Norm

## -- G --

geom_eval | Adding Test Data Layer
gg_loss | Compare Lists of Models

## -- H --

HQ | Hannan-Quinn Criterion
HQ.bvarflat | Hannan-Quinn Criterion of Multivariate Time Series Model
HQ.bvarmn | Hannan-Quinn Criterion of Multivariate Time Series Model
HQ.bvharmn | Hannan-Quinn Criterion of Multivariate Time Series Model
HQ.logLik | Hannan-Quinn Criterion
HQ.varlse | Hannan-Quinn Criterion of Multivariate Time Series Model
HQ.vharlse | Hannan-Quinn Criterion of Multivariate Time Series Model

## -- I --

init_ssvs | Initial Parameters of Stochastic Search Variable Selection (SSVS) Model
is.boundbvharemp | See if the Object a class in this package
is.bvarflat | See if the Object a class in this package
is.bvarmn | See if the Object a class in this package
is.bvharcv | See if the Object a class in this package
is.bvharemp | See if the Object a class in this package
is.bvharmn | See if the Object a class in this package
is.bvharpriorspec | See if the Object a class in this package
is.bvharspec | See if the Object a class in this package
is.predbvhar | See if the Object a class in this package
is.ssvsinit | See if the Object a class in this package
is.ssvsinput | See if the Object a class in this package
is.stable | Stability of the process
is.stable.bvarflat | Stability of VAR Coefficient Matrix
is.stable.bvarmn | Stability of VAR Coefficient Matrix
is.stable.bvharmn | Stability of VAR Coefficient Matrix
is.stable.varlse | Stability of VAR Coefficient Matrix
is.stable.vharlse | Stability of VAR Coefficient Matrix
is.varlse | See if the Object a class in this package
is.vharlse | See if the Object a class in this package

## -- K --

knit_print.boundbvharemp | Setting Empirical Bayes Optimization Bounds
knit_print.bvarflat | Fitting Bayesian VAR(p) of Flat Prior
knit_print.bvarhm | Fitting Hierarchical Bayesian VAR(p)
knit_print.bvarmn | Fitting Bayesian VAR(p) of Minnesota Prior
knit_print.bvarssvs | Fitting Bayesian VAR(p) of SSVS Prior
knit_print.bvarsv | Fitting Bayesian VAR-SV of Minnesota Belief
knit_print.bvharcv | Out-of-sample Forecasting based on Rolling Window
knit_print.bvharemp | Finding the Set of Hyperparameters of Individual Bayesian Model
knit_print.bvharirf | Impulse Response Analysis
knit_print.bvharmn | Fitting Bayesian VHAR of Minnesota Prior
knit_print.bvharpriorspec | Hyperpriors for Bayesian Models
knit_print.bvharspec | Hyperparameters for Bayesian Models
knit_print.bvharssvs | Fitting Bayesian VHAR of SSVS Prior
knit_print.bvharsv | Fitting Bayesian VHAR-SV of Minnesota Belief
knit_print.predbvhar | Forecasting Multivariate Time Series
knit_print.ssvsinit | Initial Parameters of Stochastic Search Variable Selection (SSVS) Model
knit_print.ssvsinput | Stochastic Search Variable Selection (SSVS) Hyperparameter for Coefficients Matrix and Cholesky Factor
knit_print.summary.normaliw | Summarizing Bayesian Multivariate Time Series Model
knit_print.summary.ssvsmod | Summarizing VAR and VHAR with SSVS Prior Model
knit_print.summary.varlse | Summarizing Vector Autoregressive Model
knit_print.summary.vharlse | Summarizing Vector HAR Model
knit_print.varlse | Fitting Vector Autoregressive Model of Order p Model
knit_print.vharlse | Fitting Vector Heterogeneous Autoregressive Model

## -- L --

logLik.bvarflat | Extract Log-Likelihood of Multivariate Time Series Model
logLik.bvarmn | Extract Log-Likelihood of Multivariate Time Series Model
logLik.bvharmn | Extract Log-Likelihood of Multivariate Time Series Model
logLik.varlse | Extract Log-Likelihood of Multivariate Time Series Model
logLik.vharlse | Extract Log-Likelihood of Multivariate Time Series Model

## -- M --

mae | Evaluate the Model Based on MAE (Mean Absolute Error)
mae.bvharcv | Evaluate the Model Based on MAE (Mean Absolute Error)
mae.predbvhar | Evaluate the Model Based on MAE (Mean Absolute Error)
mape | Evaluate the Model Based on MAPE (Mean Absolute Percentage Error)
mape.bvharcv | Evaluate the Model Based on MAPE (Mean Absolute Percentage Error)
mape.predbvhar | Evaluate the Model Based on MAPE (Mean Absolute Percentage Error)
mase | Evaluate the Model Based on MASE (Mean Absolute Scaled Error)
mase.bvharcv | Evaluate the Model Based on MASE (Mean Absolute Scaled Error)
mase.predbvhar | Evaluate the Model Based on MASE (Mean Absolute Scaled Error)
mrae | Evaluate the Model Based on MRAE (Mean Relative Absolute Error)
mrae.bvharcv | Evaluate the Model Based on MRAE (Mean Relative Absolute Error)
mrae.predbvhar | Evaluate the Model Based on MRAE (Mean Relative Absolute Error)
mse | Evaluate the Model Based on MSE (Mean Square Error)
mse.bvharcv | Evaluate the Model Based on MSE (Mean Square Error)
mse.predbvhar | Evaluate the Model Based on MSE (Mean Square Error)

## -- O --

oxfordman | Oxford-Man Institute Realized Library
oxfordman_rk | Oxford-Man Institute Realized Library
oxfordman_rv | Oxford-Man Institute Realized Library

## -- P --

predict.bvarflat | Forecasting Multivariate Time Series
predict.bvarmn | Forecasting Multivariate Time Series
predict.bvarssvs | Forecasting Multivariate Time Series
predict.bvarsv | Forecasting Multivariate Time Series
predict.bvharmn | Forecasting Multivariate Time Series
predict.bvharssvs | Forecasting Multivariate Time Series
predict.bvharsv | Forecasting Multivariate Time Series
predict.varlse | Forecasting Multivariate Time Series
predict.vharlse | Forecasting Multivariate Time Series
print.boundbvharemp | Setting Empirical Bayes Optimization Bounds
print.bvarflat | Fitting Bayesian VAR(p) of Flat Prior
print.bvarhm | Fitting Hierarchical Bayesian VAR(p)
print.bvarmn | Fitting Bayesian VAR(p) of Minnesota Prior
print.bvarssvs | Fitting Bayesian VAR(p) of SSVS Prior
print.bvarsv | Fitting Bayesian VAR-SV of Minnesota Belief
print.bvharcv | Out-of-sample Forecasting based on Rolling Window
print.bvharemp | Finding the Set of Hyperparameters of Individual Bayesian Model
print.bvharirf | Impulse Response Analysis
print.bvharmn | Fitting Bayesian VHAR of Minnesota Prior
print.bvharpriorspec | Hyperpriors for Bayesian Models
print.bvharspec | Hyperparameters for Bayesian Models
print.bvharssvs | Fitting Bayesian VHAR of SSVS Prior
print.bvharsv | Fitting Bayesian VHAR-SV of Minnesota Belief
print.predbvhar | Forecasting Multivariate Time Series
print.ssvsinit | Initial Parameters of Stochastic Search Variable Selection (SSVS) Model
print.ssvsinput | Stochastic Search Variable Selection (SSVS) Hyperparameter for Coefficients Matrix and Cholesky Factor
print.summary.normaliw | Summarizing Bayesian Multivariate Time Series Model
print.summary.ssvsmod | Summarizing VAR and VHAR with SSVS Prior Model
print.summary.varlse | Summarizing Vector Autoregressive Model
print.summary.vharlse | Summarizing Vector HAR Model
print.varlse | Fitting Vector Autoregressive Model of Order p Model
print.vharlse | Fitting Vector Heterogeneous Autoregressive Model

## -- R --

relmae | Evaluate the Model Based on RelMAE (Relative MAE)
relmae.bvharcv | Evaluate the Model Based on RelMAE (Relative MAE)
relmae.predbvhar | Evaluate the Model Based on RelMAE (Relative MAE)
relspne | Evaluate the Estimation Based on Relative Spectral Norm Error
relspne.bvharsp | Evaluate the Estimation Based on Relative Spectral Norm Error
residuals.bvarflat | Residual Matrix from Multivariate Time Series Models
residuals.bvarmn | Residual Matrix from Multivariate Time Series Models
residuals.bvharmn | Residual Matrix from Multivariate Time Series Models
residuals.varlse | Residual Matrix from Multivariate Time Series Models
residuals.vharlse | Residual Matrix from Multivariate Time Series Models
rmafe | Evaluate the Model Based on RMAFE
rmafe.bvharcv | Evaluate the Model Based on RMAFE
rmafe.predbvhar | Evaluate the Model Based on RMAFE
rmape | Evaluate the Model Based on RMAPE (Relative MAPE)
rmape.bvharcv | Evaluate the Model Based on RMAPE (Relative MAPE)
rmape.predbvhar | Evaluate the Model Based on RMAPE (Relative MAPE)
rmase | Evaluate the Model Based on RMASE (Relative MASE)
rmase.bvharcv | Evaluate the Model Based on RMASE (Relative MASE)
rmase.predbvhar | Evaluate the Model Based on RMASE (Relative MASE)
rmsfe | Evaluate the Model Based on RMSFE
rmsfe.bvharcv | Evaluate the Model Based on RMSFE
rmsfe.predbvhar | Evaluate the Model Based on RMSFE

## -- S --

set_bvar | Hyperparameters for Bayesian Models
set_bvar_flat | Hyperparameters for Bayesian Models
set_bvhar | Hyperparameters for Bayesian Models
set_lambda | Hyperpriors for Bayesian Models
set_psi | Hyperpriors for Bayesian Models
set_ssvs | Stochastic Search Variable Selection (SSVS) Hyperparameter for Coefficients Matrix and Cholesky Factor
set_weight_bvhar | Hyperparameters for Bayesian Models
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_ssvs_var | Generate SSVS Parameters
sim_ssvs_vhar | Generate SSVS Parameters
sim_var | Generate Multivariate Time Series Process Following VAR(p)
sim_vhar | Generate Multivariate Time Series Process Following VAR(p)
split_coef | Splitting Coefficient Matrix into List
split_coef.bvharirf | Splitting Coefficient Matrix into List
split_coef.bvharmod | Splitting Coefficient Matrix into List
spne | Evaluate the Estimation Based on Spectral Norm Error
spne.bvharsp | Evaluate the Estimation Based on Spectral Norm Error
stableroot | Roots of characteristic polynomial
stableroot.bvarflat | Characteristic polynomial roots for VAR Coefficient Matrix
stableroot.bvarmn | Characteristic polynomial roots for VAR Coefficient Matrix
stableroot.bvharmn | Characteristic polynomial roots for VAR Coefficient Matrix
stableroot.varlse | Characteristic polynomial roots for VAR Coefficient Matrix
stableroot.vharlse | Characteristic polynomial roots for VAR Coefficient Matrix
summary.normaliw | Summarizing Bayesian Multivariate Time Series Model
summary.ssvsmod | Summarizing VAR and VHAR with SSVS Prior Model
summary.varlse | Summarizing Vector Autoregressive Model
summary.vharlse | Summarizing Vector HAR Model

## -- V --

VARtoVMA | Convert VAR to VMA(infinite)
var_lm | Fitting Vector Autoregressive Model of Order p Model
VHARtoVMA | Convert VHAR to VMA(infinite)
vhar_lm | Fitting Vector Heterogeneous Autoregressive Model