spillover: h-step ahead Normalized Spillover

In bvhar: Bayesian Vector Heterogeneous Autoregressive Modeling

h-step ahead Normalized Spillover

Description

This function gives connectedness table with h-step ahead normalized spillover index (a.k.a. variance shares).

Usage

spillover(object, n_ahead = 10L, ...)

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

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

## S3 method for class 'olsmod'
spillover(object, n_ahead = 10L, ...)

## S3 method for class 'normaliw'
spillover(
  object,
  n_ahead = 10L,
  num_iter = 5000L,
  num_burn = floor(num_iter/2),
  thinning = 1L,
  ...
)

## S3 method for class 'bvarldlt'
spillover(object, n_ahead = 10L, level = 0.05, sparse = FALSE, ...)

## S3 method for class 'bvharldlt'
spillover(object, n_ahead = 10L, level = 0.05, sparse = FALSE, ...)

Arguments

object	Model object
n_ahead	step to forecast. By default, 10.
...	not used
x	bvharspillover object
digits	digit option to print
num_iter	Number to sample MNIW distribution
num_burn	Number of burn-in
thinning	Thinning every thinning-th iteration
level	Specify alpha of confidence interval level 100(1 - alpha) percentage. By default, .05.
sparse	Apply restriction. By default, FALSE.

References

Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of forecasting, 28(1), 57-66.

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