Sparse VAR (Vector Autoregression) / VECM (Vector Error Correction Model) Estimation

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Documentation for package ‘sparsevar’ version 1.0.0

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

Help Pages

sparsevar-package	sparsevar: A package to estimate multivariate time series models (such as VAR and VECM), under the sparsity hypothesis.
accuracy	Accuracy metric
bootstrapped_var	Bootstrap VAR
check_impulse_zero	Check Impulse Zero
check_is_var	Check is var
companion_var	Companion VAR
compute_forecasts	Computes forecasts for VARs
create_sparse_matrix	Create Sparse Matrix
decompose_pi	Decompose Pi VECM matrix
error_bands_irf	Error bands for IRF
fit_var	Multivariate VAR estimation
fit_varx	Multivariate VARX estimation
fit_vecm	Multivariate VECM estimation
frob_norm	Frobenius norm of a matrix
impulse_response	Impulse Response Function
inform_crit	Computes information criteria for VARs
l1norm	L1 matrix norm
l2norm	L2 matrix norm
l_infty_norm	L-infinity matrix norm
max_norm	Max-norm of a matrix
multiplot	Multiplots with ggplot
plot_irf	IRF plot
plot_irf_grid	IRF grid plot
plot_matrix	Matrix plot
plot_var	Plot VARs
plot_vecm	Plot VECMs
simulate_var	VAR simulation
simulate_varx	VARX simulation
sparsevar	sparsevar: A package to estimate multivariate time series models (such as VAR and VECM), under the sparsity hypothesis.
spectral_norm	Spectral norm
spectral_radius	Spectral radius
test_granger	Test for Ganger Causality
transform_data	Transform data
true_negative_rate	True Negative Rate
true_positive_rate	True Positive Rate
var_enet	VAR ENET
var_mcp	VAR MCP
var_scad	VAR SCAD