set_ng: Normal-Gamma Hyperparameter for Coefficients and...

In bvhar: Bayesian Vector Heterogeneous Autoregressive Modeling

Normal-Gamma Hyperparameter for Coefficients and Contemporaneous Coefficients

Description

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	Any object
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.

bvhar documentation built on April 4, 2025, 5:22 a.m.