smart_covmat: Create random VAR model (dxd) error term covariance matrix...

In sstvars: Toolkit for Reduced Form and Structural Smooth Transition Vector Autoregressive Models

Create random VAR model (dxd) error term covariance matrix \Omega fairly close to the given positive definite covariance matrix using (scaled) Wishart distribution

Description

smart_covmat generates random VAR model (dxd) error term covariance matrix \Omega from (scaled) Wishart distribution that is fairly close to the given matrix.

Usage

smart_covmat(d, Omega, accuracy)

Arguments

Omega	a symmetric positive definite (dxd) covariance matrix specifying expected value of the matrix to be generated.
accuracy	a positive real number adjusting how close to the given covariance matrix the returned individual should be. The standard deviation of each diagonal element is... \omega_{i,i}/accuracy when accuracy > d/2 and sqrt(2/d)*\omega_{i,i} when accuracy <= d/2. Wishart distribution is used for reduced form models, but for more details read the source code.

Value

Returns a (d(d+1)/2x1) vector containing vech-vectorized covariance matrix \Omega.

sstvars documentation built on April 11, 2025, 5:47 p.m.