Bayesian Vector Heterogeneous Autoregressive Modeling

Documentation for package ‘bvhar’ version 1.0.0

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-- 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