random_coefmats: Create random VAR-model (dxd) coefficient matrices A.
In gmvarkit: Estimate Gaussian and Student's t Mixture Vector Autoregressive Models

random_coefmats

R Documentation

Create random VAR-model `(dxd)` coefficient matrices `A`.

Description

random_coefmats generates random VAR model coefficient matrices.

Usage

random_coefmats(d, how_many, scale)

Arguments

`d`	the number of time series in the system.
`how_many`	how many `(dxd)` coefficient matrices `A` should be drawn?
`scale`	non-diagonal elements will be drawn from mean zero normal distribution with `sd=0.3/scale` and diagonal elements from one with `sd=0.6/scale`. Larger scale will hence more likely result stationary coefficient matrices, but will explore smaller area of the parameter space. Can be for example `1 + log(2*mean(c((p-0.2)^(1.25), d)))`.

Value

Returns ((how_many*d^2)x1) vector containing vectorized coefficient matrices (vec(A_{1}),...,vec(A_{how_many})). Note that if how_many==p, then the returned vector equals \phi_{m}.

gmvarkit documentation built on April 4, 2025, 1:54 a.m.