irf.linear | R Documentation |
Compute the impulse response coefficients (IRF) of a VAR(p) (or transformed VECM to VAR(p)) for
n.ahead
steps.
For TVECM and TVAR model, argument regime
offers regime-specific IRF.
## S3 method for class 'linear' irf( x, impulse = NULL, response = NULL, n.ahead = 10, ortho = TRUE, cumulative = FALSE, boot = TRUE, ci = 0.95, runs = 100, seed = NULL, ... ) ## S3 method for class 'setar' irf( x, impulse = NULL, response = NULL, n.ahead = 10, ortho = TRUE, cumulative = FALSE, boot = TRUE, ci = 0.95, runs = 100, seed = NULL, regime = c("L", "M", "H"), ... ) ## S3 method for class 'ar' irf( x, impulse = NULL, response = NULL, n.ahead = 10, ortho = TRUE, cumulative = FALSE, boot = TRUE, ci = 0.95, runs = 100, seed = NULL, ... ) ## S3 method for class 'VAR' irf( x, impulse = NULL, response = NULL, n.ahead = 10, ortho = TRUE, cumulative = FALSE, boot = TRUE, ci = 0.95, runs = 100, seed = NULL, ... ) ## S3 method for class 'VECM' irf( x, impulse = NULL, response = NULL, n.ahead = 10, ortho = TRUE, cumulative = FALSE, boot = TRUE, ci = 0.95, runs = 100, seed = NULL, ... ) ## S3 method for class 'TVAR' irf( x, impulse = NULL, response = NULL, n.ahead = 10, ortho = TRUE, cumulative = FALSE, boot = TRUE, ci = 0.95, runs = 100, seed = NULL, regime = c("L", "M", "H"), ... ) ## S3 method for class 'TVECM' irf( x, impulse = NULL, response = NULL, n.ahead = 10, ortho = TRUE, cumulative = FALSE, boot = TRUE, ci = 0.95, runs = 100, seed = NULL, regime = c("L", "M", "H"), ... )
x |
Object of class ‘ |
impulse, response |
Not used! |
n.ahead |
Integer specifying the steps. |
ortho |
Logical, if |
cumulative |
Logical, if |
boot, ci, runs, seed |
Arguments for the bootstrap, see |
... |
Currently not used. |
regime |
For a setar model, which regime (L, M or H) to produce IRF for? |
A list of class ‘varirf
’ see irf.varest
Matthieu Stigler
plot
for the plot method. lineVar
,
VECM
for the models.
Hamilton, J. (1994), Time Series Analysis, Princeton University
Press, Princeton.
Lutkepohl, H. (2006), New Introduction to Multiple Time Series Analysis, Springer, New York.
data(barry) ## For VAR mod_var <- lineVar(barry, lag = 2) irf(mod_var, impulse = "dolcan", response = c("dolcan", "cpiUSA", "cpiCAN"), boot = FALSE) ## For VECM mod_VECM <- VECM(barry, lag = 2, estim="ML", r=2) irf(mod_VECM, impulse = "dolcan", response = c("dolcan", "cpiUSA", "cpiCAN"), boot = FALSE)
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