summary.bvarlist: Summarising Bayesian VAR or VEC Models

In franzmohr/bvartools: Bayesian Inference of Vector Autoregressive and Error Correction Models

Summarising Bayesian VAR or VEC Models

Description

summary method for class "bvarlist".

Usage

## S3 method for class 'bvarlist'
summary(object, ...)

Arguments

object	an object of class "bvar", usually, a result of a call to draw_posterior.
...	further arguments passed to or from other methods.

Details

The log-likelihood for the calculation of the information criteria is obtained by

LL = \frac{1}{R} \sum_{i = 1}^{R} \left( \sum_{t = 1}^{T} -\frac{K}{2} \ln 2\pi - \frac{1}{2} \ln |\Sigma_t^{(i)}| -\frac{1}{2} (u_t^{{(i)}\prime} (\Sigma_t^{(i)})^{-1} u_t^{(i)} \right)

, where u_t = y_t - \mu_t. The Akaike, Bayesian and Hannan–Quinn (HQ) information criteria are calculated as

AIC = 2 (Kp + Ms + N) - 2 LL

,

BIC = (Kp + Ms + N) ln(T) - 2 LL

and

HQ = 2 (Kp + Ms + N) ln(ln(T)) - 2 LL

, respectively, where K is the number of endogenous variables, p the number of lags of endogenous variables, M the number of exogenous variables, s the number of lags of exogenous variables, N the number of deterministic terms and T the number of observations.

Value

summary.bvarlist returns a table of class "summary.bvarlist".

franzmohr/bvartools documentation built on Jan. 28, 2024, 4:06 a.m.