A B C D E F G H I K L M P R S V
AIC.bvarflat | Fitting Bayesian VAR(p) of Flat Prior |
AIC.bvarmn | Fitting Bayesian VAR(p) of Minnesota Prior |
AIC.bvharmn | Fitting Bayesian VHAR of Minnesota Prior |
AIC.varlse | Fitting Vector Autoregressive Model of Order p Model |
AIC.vharlse | Fitting Vector Heterogeneous Autoregressive Model |
alpl | Evaluate the Density Forecast Based on Average Log Predictive Likelihood (APLP) |
alpl.bvharcv | Evaluate the Density Forecast Based on Average Log Predictive Likelihood (APLP) |
autolayer.predbvhar | Plot Forecast Result |
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 |
BIC.bvarflat | Fitting Bayesian VAR(p) of Flat Prior |
BIC.bvarmn | Fitting Bayesian VAR(p) of Minnesota Prior |
BIC.bvharmn | Fitting Bayesian VHAR of Minnesota Prior |
BIC.varlse | Fitting Vector Autoregressive Model of Order p Model |
BIC.vharlse | Fitting Vector Heterogeneous Autoregressive 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_bvhar | 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 |
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 |
divide_ts | Split a Time Series Dataset into Train-Test Set |
dynamic_spillover | Dynamic Spillover |
dynamic_spillover.ldltmod | Dynamic Spillover |
dynamic_spillover.normaliw | Dynamic Spillover |
dynamic_spillover.olsmod | Dynamic Spillover |
dynamic_spillover.svmod | Dynamic Spillover |
etf_vix | CBOE ETF Volatility Index Dataset |
fitted | Fitted Matrix from Multivariate Time Series Models |
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_expand.ldltmod | Out-of-sample Forecasting based on Expanding Window |
forecast_expand.normaliw | Out-of-sample Forecasting based on Expanding Window |
forecast_expand.olsmod | Out-of-sample Forecasting based on Expanding Window |
forecast_expand.svmod | Out-of-sample Forecasting based on Expanding Window |
forecast_roll | Out-of-sample Forecasting based on Rolling Window |
forecast_roll.ldltmod | Out-of-sample Forecasting based on Rolling Window |
forecast_roll.normaliw | Out-of-sample Forecasting based on Rolling Window |
forecast_roll.olsmod | Out-of-sample Forecasting based on Rolling Window |
forecast_roll.svmod | Out-of-sample Forecasting based on Rolling Window |
FPE | Final Prediction Error Criterion |
FPE.varlse | Final Prediction Error Criterion |
FPE.vharlse | Final Prediction Error Criterion |
fromse | Evaluate the Estimation Based on Frobenius Norm |
fromse.bvharsp | Evaluate the Estimation Based on Frobenius Norm |
geom_eval | Adding Test Data Layer |
gg_loss | Compare Lists of Models |
HQ | Hannan-Quinn Criterion |
HQ.bvarflat | Hannan-Quinn Criterion |
HQ.bvarmn | Hannan-Quinn Criterion |
HQ.bvharmn | Hannan-Quinn Criterion |
HQ.logLik | Hannan-Quinn Criterion |
HQ.varlse | Hannan-Quinn Criterion |
HQ.vharlse | Hannan-Quinn Criterion |
irf | Impulse Response Analysis |
irf.varlse | Impulse Response Analysis |
irf.vharlse | Impulse Response Analysis |
is.boundbvharemp | Setting Empirical Bayes Optimization Bounds |
is.bvarflat | Fitting Bayesian VAR(p) of Flat Prior |
is.bvarmn | Fitting Bayesian VAR(p) of Minnesota Prior |
is.bvharcv | Out-of-sample Forecasting based on Rolling Window |
is.bvharemp | Finding the Set of Hyperparameters of Individual Bayesian Model |
is.bvharirf | Impulse Response Analysis |
is.bvharmn | Fitting Bayesian VHAR of Minnesota Prior |
is.bvharmod | Fitting Vector Autoregressive Model of Order p Model |
is.bvharpriorspec | Hyperpriors for Bayesian Models |
is.bvharspec | Hyperparameters for Bayesian Models |
is.covspec | Covariance Matrix Prior Specification |
is.dlspec | Dirichlet-Laplace Hyperparameter for Coefficients and Contemporaneous Coefficients |
is.gdpspec | Generalized Double Pareto Shrinkage Hyperparameters for Coefficients and Contemporaneous Coefficients |
is.horseshoespec | Horseshoe Prior Specification |
is.interceptspec | Prior for Constant Term |
is.ldltspec | Covariance Matrix Prior Specification |
is.ngspec | Normal-Gamma Hyperparameter for Coefficients and Contemporaneous Coefficients |
is.predbvhar | Forecasting Multivariate Time Series |
is.ssvsinput | Stochastic Search Variable Selection (SSVS) Hyperparameter for Coefficients Matrix and Cholesky Factor |
is.stable | Stability of the process |
is.stable.bvarflat | Stability of the process |
is.stable.bvarmn | Stability of the process |
is.stable.bvharmn | Stability of the process |
is.stable.varlse | Stability of the process |
is.stable.vharlse | Stability of the process |
is.svspec | Covariance Matrix Prior Specification |
is.varlse | Fitting Vector Autoregressive Model of Order p Model |
is.vharlse | Fitting Vector Heterogeneous Autoregressive Model |
knit_print.boundbvharemp | Setting Empirical Bayes Optimization Bounds |
knit_print.bvarflat | Fitting Bayesian VAR(p) of Flat Prior |
knit_print.bvarhm | Fitting Bayesian VAR(p) of Minnesota Prior |
knit_print.bvarldlt | Fitting Bayesian VAR with Coefficient and Covariance Prior |
knit_print.bvarmn | Fitting Bayesian VAR(p) of Minnesota Prior |
knit_print.bvarsv | Fitting Bayesian VAR with Coefficient and Covariance Prior |
knit_print.bvharcv | Out-of-sample Forecasting based on Rolling Window |
knit_print.bvhardynsp | Dynamic Spillover |
knit_print.bvharemp | Finding the Set of Hyperparameters of Individual Bayesian Model |
knit_print.bvharhm | Fitting Bayesian VHAR of Minnesota Prior |
knit_print.bvharirf | Impulse Response Analysis |
knit_print.bvharldlt | Fitting Bayesian VHAR with Coefficient and Covariance Prior |
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.bvharspillover | h-step ahead Normalized Spillover |
knit_print.bvharsv | Fitting Bayesian VHAR with Coefficient and Covariance Prior |
knit_print.horseshoespec | Horseshoe Prior Specification |
knit_print.interceptspec | Prior for Constant Term |
knit_print.predbvhar | Forecasting Multivariate Time Series |
knit_print.ssvsinput | Stochastic Search Variable Selection (SSVS) Hyperparameter for Coefficients Matrix and Cholesky Factor |
knit_print.summary.bvharsp | Summarizing BVAR and BVHAR with Shrinkage Priors |
knit_print.summary.normaliw | Summarizing Bayesian Multivariate Time Series 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 |
logLik.bvarflat | Fitting Bayesian VAR(p) of Flat Prior |
logLik.bvarmn | Fitting Bayesian VAR(p) of Minnesota Prior |
logLik.bvharmn | Fitting Bayesian VHAR of Minnesota Prior |
logLik.varlse | Fitting Vector Autoregressive Model of Order p Model |
logLik.vharlse | Fitting Vector Heterogeneous Autoregressive Model |
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) |
predict | Forecasting Multivariate Time Series |
predict.bvarflat | Forecasting Multivariate Time Series |
predict.bvarldlt | Forecasting Multivariate Time Series |
predict.bvarmn | Forecasting Multivariate Time Series |
predict.bvarsv | Forecasting Multivariate Time Series |
predict.bvharldlt | Forecasting Multivariate Time Series |
predict.bvharmn | 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 Bayesian VAR(p) of Minnesota Prior |
print.bvarldlt | Fitting Bayesian VAR with Coefficient and Covariance Prior |
print.bvarmn | Fitting Bayesian VAR(p) of Minnesota Prior |
print.bvarsv | Fitting Bayesian VAR with Coefficient and Covariance Prior |
print.bvharcv | Out-of-sample Forecasting based on Rolling Window |
print.bvhardynsp | Dynamic Spillover |
print.bvharemp | Finding the Set of Hyperparameters of Individual Bayesian Model |
print.bvharhm | Fitting Bayesian VHAR of Minnesota Prior |
print.bvharirf | Impulse Response Analysis |
print.bvharldlt | Fitting Bayesian VHAR with Coefficient and Covariance Prior |
print.bvharmn | Fitting Bayesian VHAR of Minnesota Prior |
print.bvharpriorspec | Hyperpriors for Bayesian Models |
print.bvharspec | Hyperparameters for Bayesian Models |
print.bvharspillover | h-step ahead Normalized Spillover |
print.bvharsv | Fitting Bayesian VHAR with Coefficient and Covariance Prior |
print.covspec | Covariance Matrix Prior Specification |
print.dlspec | Dirichlet-Laplace Hyperparameter for Coefficients and Contemporaneous Coefficients |
print.horseshoespec | Horseshoe Prior Specification |
print.interceptspec | Prior for Constant Term |
print.ngspec | Normal-Gamma Hyperparameter for Coefficients and Contemporaneous Coefficients |
print.predbvhar | Forecasting Multivariate Time Series |
print.ssvsinput | Stochastic Search Variable Selection (SSVS) Hyperparameter for Coefficients Matrix and Cholesky Factor |
print.summary.bvharsp | Summarizing BVAR and BVHAR with Shrinkage Priors |
print.summary.normaliw | Summarizing Bayesian Multivariate Time Series 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 |
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 | Residual Matrix from Multivariate Time Series Models |
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 |
set_bvar | Hyperparameters for Bayesian Models |
set_bvar_flat | Hyperparameters for Bayesian Models |
set_bvhar | Hyperparameters for Bayesian Models |
set_dl | Dirichlet-Laplace Hyperparameter for Coefficients and Contemporaneous Coefficients |
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_psi | Hyperpriors for Bayesian Models |
set_ssvs | Stochastic Search Variable Selection (SSVS) Hyperparameter for Coefficients Matrix and Cholesky Factor |
set_sv | Covariance Matrix Prior Specification |
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_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 |
spillover.bvarldlt | h-step ahead Normalized Spillover |
spillover.bvharldlt | h-step ahead Normalized Spillover |
spillover.normaliw | h-step ahead Normalized Spillover |
spillover.olsmod | h-step ahead Normalized Spillover |
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 | Roots of characteristic polynomial |
stableroot.bvarmn | Roots of characteristic polynomial |
stableroot.bvharmn | Roots of characteristic polynomial |
stableroot.varlse | Roots of characteristic polynomial |
stableroot.vharlse | Roots of characteristic polynomial |
summary.bvharsp | Summarizing BVAR and BVHAR with Shrinkage Priors |
summary.hsmod | Summarizing BVAR and BVHAR with Shrinkage Priors |
summary.ngmod | Summarizing BVAR and BVHAR with Shrinkage Priors |
summary.normaliw | Summarizing Bayesian Multivariate Time Series Model |
summary.ssvsmod | Summarizing BVAR and BVHAR with Shrinkage Priors |
summary.varlse | Summarizing Vector Autoregressive Model |
summary.vharlse | Summarizing Vector HAR Model |
VARtoVMA | Convert VAR to VMA(infinite) |
var_bayes | Fitting Bayesian VAR with Coefficient and Covariance Prior |
var_lm | Fitting Vector Autoregressive Model of Order p Model |
VHARtoVMA | Convert VHAR to VMA(infinite) |
vhar_bayes | Fitting Bayesian VHAR with Coefficient and Covariance Prior |
vhar_lm | Fitting Vector Heterogeneous Autoregressive Model |