check_stability: Check the stability criterion of a VAR(p) model

In nielsaka/zeitreihe: Simulate, Estimate, Select, and Forecast Multiple Time Series Processes

Description

This function will check whether the process implied by the coefficient matrix A is stable. That is, whether the eigenvalues of the associated companion format are all smaller than one in absolute terms.

Usage

check_stability(A)

Arguments

A	A (K x Kp) matrix, providing the coeffcients for lag 1 to p with the first row containing the coefficents of the first equation. Parameter p is the maximum lag length and K the number of variables.

Value

Boolean scalar. TRUE if the criterion is satisfied, otherwise FALSE.

Examples

A <- matrix(c(.5, .4, .1, .5, 0, .25, 0, 0), nrow = 2)
check_stability(A)

A <- matrix(c(1, 0, 0, 1), nrow = 2)
check_stability(A)

A <- matrix(c(1, 0, 0, 1, -0.1, 0, 0, -0.1), nrow = 2)
check_stability(A)

nielsaka/zeitreihe documentation built on March 17, 2020, 8:38 p.m.