favar: Factor-Augmented Vector Autoregression

In kvasilopoulos/abvar: Vector Autoregression Models

Description

Factor-Augmented Vector Autoregression

Usage

favar(
  data,
  priorObj,
  factordata,
  nreps,
  burnin,
  alpha,
  beta,
  tau2,
  c2,
  li_prvar,
  priorm,
  stabletest = TRUE,
  nthin = 1
)

Arguments

data	data that is not going to be reduced to factors
priorObj	An S3 object containing information about the prior.
factordata	data that is going to be reduced to its factors
nreps	total number of draws
burnin	number of burn-in draws.
alpha, beta	prior on the variance of the measurement equation
tau2	variance of the coefficients in the measurement equation (only used if priorm=2)
c2	factor for the variance of the coefficients (only used if priorm=2)
li_prvar	prior on variance of coefficients (only used if priorm = 1)
priorm	Selects the prior on the measurement equation, 1=Normal-Gamma Prior and 2=SSVS prior.
stabletest	boolean, check if a draw is stationary or not
nthin	thinning parameter

kvasilopoulos/abvar documentation built on April 27, 2021, 6:38 a.m.