| 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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