VARshrink v0.3.1

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Shrinkage Estimation Methods for Vector Autoregressive Models

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>.

Readme

VARshrink: Shrinkage Estimation Methods for Vector Autoregressive (VAR) Models.

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.

The package VARshrink aims to be an integrative R package delivering nonparametric, parametric, and semiparametric methods in a unified and consistent manner.

The package VARshrink provides a simple interface function VARshrink(), which is an extension of the function VAR() in the vars package.

Example:

data(Canada, package = "vars")
y <- diff(Canada)
estim <- VARshrink(y, p = 2, type = "const", method = "ns")
plot(predict(estim), names = "U")

References

N. Lee, H. Choi, and S.-H. Kim (2016). Bayes shrinkage estimation for high-dimensional VAR models with scale mixture of normal distributions for noise. Computational Statistics & Data Analysis 101, 250-276. doi: 10.1016/j.csda.2016.03.007

S. Ni and D. Sun (2005). Bayesian estimates for vector autoregressive models. Journal of Business & Economic Statistics 23(1), 105-117. doi: 10.1198/073500104000000622

R. Opgen-Rhein and K. Strimmer (2007). Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregressive process. BMC Bioinformatics 8(2), S3. doi: 10.1186/1471-2105-8-S2-S3.

Functions in VARshrink

Name Description
lm_multiv_ridge Multivariate Ridge Regression
lm_full_Bayes_SR Full Bayesian Shrinkage Estimation Method for Multivariate Regression
lm_ShVAR_KCV K-fold Cross Validation for Selection of Shrinkage Parameters of Semiparametric Bayesian Shrinkage Estimator for Multivariate Regression
irf.varshrinkest Impulse response function
restrict_sh Restricted VAR
arch.test_sh ARCH-LM test
print.varshsum Print method for class "varshsum"
fevd.varshrinkest Forecast Error Variance Decomposition
normality.test_sh Normality, multivariate skewness and kurtosis test
logLik.varshrinkest Log-likelihood method for class "varshrinkest"
roots_sh Eigenvalues of the companion coefficient matrix of a VAR(p)-process
serial.test_sh Test for serially correlated errors for VAR shrinkage estimate
predict.varshrinkest Predict method for objects of class varshrinkest
lm_semi_Bayes_PCV Semiparametric Bayesian Shrinkage Estimation Method for Multivariate Regression
stability_sh Stability function
summary.shrinklm Summary method for class "shrinklm"
summary.varshrinkest Summary method for an object of class 'varshrinkest', VAR parameters estimated by VARshrink()
simVARmodel Generate multivariate time series data using the given VAR model
shrinkVARcoef Semiparametric Bayesian Shrinkage Estimator for Multivariate Regression
print.varshrinkest Print method for class "varshrinkest"
Acoef_sh Coefficient matrices of endogenous variables
causality_sh Causality Analysis for class "varshrinkest"
calcSSE_Acoef Sum of squared errors (SSE) between coefficients of two VARs
BQ_sh BQ function for class "varshrinkest"
convPsi2varresult Convert format for VAR coefficients from Psi to varresult
Phi.varshrinkest Coefficient matrices of the MA represention
Bcoef_sh Coefficient matrix
createVARCoefs_ltriangular Create coefficients of a VAR model
VARshrink Shrinkage estimation of VAR parameters
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Vignettes of VARshrink

Name
article_html_varshrink.Rmd
bibVARshrink.bib
table3_modelcomp.RData
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Details

License GPL-3
URL https://github.com/namgillee/VARshrink/
BugReports https://github.com/namgillee/VARshrink/issues/
Encoding UTF-8
LazyData true
RoxygenNote 6.1.1
VignetteBuilder knitr
NeedsCompilation no
Packaged 2019-10-07 13:31:17 UTC; namgi
Repository CRAN
Date/Publication 2019-10-09 15:10:03 UTC

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