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