print.summary.bvharsp {bvhar}

Summarizing BVAR and BVHAR with Shrinkage Priors

Description

Conduct variable selection.

Usage

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

## S3 method for class 'summary.ssvsmod'
knit_print(x, ...)

## S3 method for class 'ssvsmod'
summary(object, method = c("pip", "ci"), threshold = 0.5, level = 0.05, ...)

## S3 method for class 'hsmod'
summary(object, method = c("ci", "pip"), threshold = 0.5, level = 0.05, ...)

Arguments

x

summary.ssvsmod object

digits

digit option to print

...

not used

object

ssvsmod object

method

Use PIP ("pip") or credible interval ("ci").

threshold

Threshold for posterior inclusion probability

level

Specify alpha of credible interval level 100(1 - alpha) percentage. By default, .05.

Value

summary.ssvsmod object

summary.hsmod object

References

George, E. I., & McCulloch, R. E. (1993). Variable Selection via Gibbs Sampling. Journal of the American Statistical Association, 88(423), 881–889.

George, E. I., Sun, D., & Ni, S. (2008). Bayesian stochastic search for VAR model restrictions. Journal of Econometrics, 142(1), 553–580.

Koop, G., & Korobilis, D. (2009). Bayesian Multivariate Time Series Methods for Empirical Macroeconomics. Foundations and Trends® in Econometrics, 3(4), 267–358.

O’Hara, R. B., & Sillanpää, M. J. (2009). A review of Bayesian variable selection methods: what, how and which. Bayesian Analysis, 4(1), 85–117.