The BVAR package is used to create basic types of prior dummy observations when estimating Bayesian VAR models. The dummy observations are passed in the VAR/estimate
function through the 'BVAR='
option.
covmat
- Covariance matrix prior dummy observations for BVARs.litterman
- Litterman's prior dummy observations for BVARs.sumofcoeff
- Doan et al sum-of-coefficient prior dummy observations for BVARs.uncmean
- Unconditional-mean dummy (or Sims' initial dummy) observations for BVARs.user
- User-supplied prior dummy observations for BVARs.The prior dummies produced by litterman
, uncmean
, sumofcoeff
can be weighted up or down using the input argument Mu
. To give the weight a clear interpretation, use the option 'stdize=' true
when estimating the VAR. In that case, setting Mu
to sqrt(N)
means the prior dummies are worth a total of extra N
artifical observations; the weight can be related to the actual number of observations used in estimation.
help BVAR
help BVAR/function_name