simVARmodel

Generate a multivariate time series data set using the given VAR model.

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>.

Namgil Lee

VARshrink

Shrinkage Estimation Methods for Vector Autoregressive Models

Heon Young Yang

Sung-Ho Kim

simVARmodel function

<dl><dt>numT</dt>
<dd>Number of observed time points, T.</dd>
<dt>model</dt>
<dd>A list object with Coef, Sigma, dof;
Coef is a list with A and c; A is a list object of K-by-K coefficient
matrices and c is a length-K vector.
Sigma is a K-by-K scale matrix and
dof is a degree of freedom for multivariate t-distribution for noise.</dd>
<dt>burnin</dt>
<dd>Number of initial points which are not included in the final
values.</dd></dl>

Arguments

Generate multivariate time series data using the given VAR model — simVARmodel

<dl>

<dt>numT</dt>
<dd>Number of observed time points, T.</dd>


<dt>model</dt>
<dd>A list object with Coef, Sigma, dof;
Coef is a list with A and c; A is a list object of K-by-K coefficient
matrices and c is a length-K vector.
Sigma is a K-by-K scale matrix and
dof is a degree of freedom for multivariate t-distribution for noise.</dd>


<dt>burnin</dt>
<dd>Number of initial points which are not included in the final
values.</dd>

</dl>

simVARmodel: Generate multivariate time series data using the given VAR model

Description

Usage

Value

Arguments

Details

Examples