set up Minnesota Prior

Source: R/prior.r

set up Minnesota Prior

set_prior_minnesota(mydata, factordata = NULL, no_factors = 0, nolags,
  intercept = TRUE, lambda1 = 1, lambda2 = 1, lambda3 = 1,
  lambda4 = 2)

Arguments

mydata

data
factordata

data for factor models
no_factors

number of factors (not yet implemented)
nolags

number of lags (not yet implemented)
intercept

whether the model has an intercept
lambda1

hyperparameter 1
lambda2

hyperparameter 2
lambda3

hyperparameter 3
lambda4

hyperparameter 4

Value

returns an S3 object of the class ""minnesota"

References

K. Rao Kadiyala and Sune Karlsson, Numerical Methods for Estimation and Inference in Bayesian VAR-Models, Journal of Applied Econometrics 12(2), 99-132

Gary Koop and Dimitris Korobilis (2010), Bayesian Multivariate Time Series Methods for Empirical Macroeconomics, Foundations and Trends in Econometrics 3(4), 267-358

Thomas Doan, Robert Litterman, Christopher A. Sims (1984), Forecasting and conditional projection using realistic prior distributions, Econometric Reviews 3(1), 1-100