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VARshrink
View on CRAN: Click
here
Download and install VARshrink package within the R console
Install from CRAN:
install.packages("VARshrink")
Install from Github:
library("remotes")
install_github("cran/VARshrink") Install by package version:
library("remotes")
install_version("VARshrink", "0.3.3") Attach the package and use:
library("VARshrink")
Maintained by
Namgil Lee
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-10-09
Latest Update: 2019-10-09
Description:
Vector autoregressive (VAR) model is a fundamental and effective approach for multivariate time series analysis. Shrinkage estimation methods can be applied to high-dimensional VAR models with dimensionality greater than the number of observations, contrary to the standard ordinary least squares method. This package is an integrative package delivering nonparametric, parametric, and semiparametric methods in a unified and consistent manner, such as the multivariate ridge regression in Golub, Heath, and Wahba (1979) <doi:10.2307/1268518>, a James-Stein type nonparametric shrinkage method in Opgen-Rhein and Strimmer (2007) <doi:10.1186/1471-2105-8-S2-S3>, and Bayesian estimation methods using noninformative and informative priors in Lee, Choi, and S.-H. Kim (2016) <doi:10.1016/j.csda.2016.03.007> and Ni and Sun (2005) <doi:10.1198/073500104000000622>.
How to cite:
Namgil Lee (2019). VARshrink: Shrinkage Estimation Methods for Vector Autoregressive Models. R package version 0.3.3, https://cran.r-project.org/web/packages/VARshrink. Accessed 07 Jun. 2026.
Previous versions and publish date:
0.3.1 (2019-10-09 17:10)
Other packages that cited VARshrink R package
View VARshrink citation profile
Other R packages that VARshrink depends,
imports, suggests or enhances
Complete documentation for VARshrink
Functions, R codes and Examples using
the VARshrink R package
Some associated functions: Acoef_sh . BQ_sh . Bcoef_sh . Phi.varshrinkest . VARshrink . arch.test_sh . calcSSE_Acoef . causality_sh . convPsi2varresult . createVARCoefs_ltriangular . fevd.varshrinkest . irf.varshrinkest . lm_ShVAR_KCV . lm_full_Bayes_SR . lm_multiv_ridge . lm_semi_Bayes_PCV . logLik.varshrinkest . normality.test_sh . predict.varshrinkest . print.varshrinkest . print.varshsum . restrict_sh . roots_sh . serial.test_sh . shrinkVARcoef . simVARmodel . stability_sh . summary.shrinklm . summary.varshrinkest .
Some associated R codes: Acoef_sh.R . BQ_sh.R . Bcoef_sh.R . Phi.varshrinkest.R . Psi.varshrinkest.R . VARshrink.R . arch.test_sh.R . calcSSE_Acoef.R . causality_sh.R . convPsi2varresult.R . createVARCoefs_ltriangular.R . fevd.varshrinkest.R . h_boot.R . h_fecov.R . h_irf.R . irf.varshrinkest.R . lm_ShVAR_KCV.R . lm_full_Bayes_SR.R . lm_multiv_ridge.R . lm_semi_Bayes_PCV.R . logLik.varshrinkest.R . normality.test_sh.R . plot.varshirf.R . predict.varshrinkest.R . print.varshrinkest.R . print.varshsum.R . restrict_sh.R . roots_sh.R . serial.test_sh.R . shrinkVARcoef.R . simVARmodel.R . stability_sh.R . summary.shrinklm.R . summary.varshrinkest.R . Full VARshrink package functions and examples
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