View source: R/boot_after_boot.R
ba.boot | R Documentation |
Bootstrap intervals based on bias-adjusted estimators
ba.boot(x, nc = 1)
x |
SVAR object of class "sboot" |
nc |
Integer. Number of processor cores |
A list of class "sboot" with elements
true |
Point estimate of impulse response functions |
bootstrap |
List of length "nboot" holding bootstrap impulse response functions |
SE |
Bootstrapped standard errors of estimated covariance decomposition (only if "x" has method "Cramer von-Mises", or "Distance covariances") |
nboot |
Number of bootstrap iterations |
b_length |
Length of each block |
point_estimate |
Point estimate of covariance decomposition |
boot_mean |
Mean of bootstrapped covariance decompositions |
signrest |
Evaluated sign pattern |
sign_complete |
Frequency of appearance of the complete sign pattern in all bootstrapped covariance decompositions |
sign_part |
Frequency of bootstrapped covariance decompositions which conform the complete predetermined sign pattern. If signrest=NULL, the frequency of bootstrapped covariance decompositions that hold the same sign pattern as the point estimate is provided. |
sign_part |
Frequency of single shocks in all bootstrapped covariance decompositions which accord to a specific predetermined sign pattern |
cov_bs |
Covariance matrix of bootstrapped parameter in impact relations matrix |
method |
Used bootstrap method |
VAR |
Estimated input VAR object |
Kilian, L. (1998). Small-sample confidence intervals for impulse response functions. Review of Economics and Statistics 80, 218-230.
mb.boot
, wild.boot
# data contains quarterly observations from 1965Q1 to 2008Q3 # x = output gap # pi = inflation # i = interest rates set.seed(23211) v1 <- vars::VAR(USA, lag.max = 10, ic = "AIC" ) x1 <- id.dc(v1) summary(x1) # Bootstrap bb <- mb.boot(x1, b.length = 15, nboot = 300, n.ahead = 30, nc = 1, signrest = NULL) summary(bb) plot(bb, lowerq = 0.16, upperq = 0.84) # Bias-adjusted bootstrap bb2 <- ba.boot(bb, nc = 1) plot(bb2, lowerq = 0.16, upperq = 0.84)
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