Normal-Gamma Hyperparameter for Coefficients and Contemporaneous Coefficients

Set NG hyperparameters for VAR or VHAR coefficient and contemporaneous coefficient.

Usage

set_ng(
  shape_sd = 0.01,
  group_shape = 0.01,
  group_scale = 0.01,
  global_shape = 0.01,
  global_scale = 0.01,
  contem_global_shape = 0.01,
  contem_global_scale = 0.01
)

# S3 method for class 'ngspec'
print(x, digits = max(3L, getOption("digits") - 3L), ...)

is.ngspec(x)

Arguments

shape_sd

Standard deviation used in MH of Gamma shape

group_shape

Inverse gamma prior shape for coefficient group shrinkage

group_scale

Inverse gamma prior scale for coefficient group shrinkage

global_shape

Inverse gamma prior shape for coefficient global shrinkage

global_scale

Inverse gamma prior scale for coefficient global shrinkage

contem_global_shape

Inverse gamma prior shape for contemporaneous coefficient global shrinkage

contem_global_scale

Inverse gamma prior scale for contemporaneous coefficient global shrinkage

x

ngspec

digits

digit option to print

...

not used

Value

ngspec object

References

Chan, J. C. C. (2021). Minnesota-type adaptive hierarchical priors for large Bayesian VARs. International Journal of Forecasting, 37(3), 1212-1226.

Huber, F., & Feldkircher, M. (2019). Adaptive Shrinkage in Bayesian Vector Autoregressive Models. Journal of Business & Economic Statistics, 37(1), 27-39.

Korobilis, D., & Shimizu, K. (2022). Bayesian Approaches to Shrinkage and Sparse Estimation. Foundations and Trends® in Econometrics, 11(4), 230-354.