R: Summary method for objects of class varest, svarest and...
summary
R Documentation
Summary method for objects of class varest, svarest and svecest
Description
'summary' methods for class '"varest"', '"svarest"' and '"svecest"'.
Usage
## S3 method for class 'varest'
summary(object, equations = NULL, ...)
## S3 method for class 'varsum'
print(x, digits = max(3, getOption("digits") - 3),
signif.stars = getOption("show.signif.stars"), ...)
## S3 method for class 'svarest'
summary(object, ...)
## S3 method for class 'svarsum'
print(x, digits = max(3, getOption("digits") - 3), ...)
## S3 method for class 'svecest'
summary(object, ...)
## S3 method for class 'svecsum'
print(x, digits = max(3, getOption("digits") - 3), ...)
Arguments
object
Object of class ‘varest’, usually, a
result of a call to VAR, or object of class ‘svarest’, usually, a
result of a call to SVAR, or object of class ‘svecest’, usually, a
result of a call to SVEC.
equations
Character vector of endogenous variable names for
which summary results should be returned. The default is NULL
and results are returned for all equations in the VAR.
x
Object with class attribute ‘varsum’, ‘svarsum’.
digits
the number of significant digits to use when printing.
signif.stars
logical. If 'TRUE', ‘significance stars’
are printed for each coefficient.
...
further arguments passed to or from other methods.
Value
Returns either a list with class attribute varsum which contains the
following elements:
names
Character vector with the names of the endogenous
correlation matrix of VAR residuals.
logLik
Numeric, value of log Likelihood.
obs
Integer, sample size.
roots
Vector, roots of the characteristic polynomial.
type
Character vector, deterministic regressors included in VAR:
call
Call, the initial call to VAR.
Or a list with class attribute svarsum which contains the
following elements:
type
Character, the type of SVAR-model.
A
Matrix, estimated coefficients for A matrix.
B
Matrix, estimated coefficients for B matrix.
Ase
Matrix, standard errors for A matrix.
Bse
Matrix, standard errors for B matrix.
LRIM
Matrix, long-run impact coefficients for BQ.
Sigma.U
Matrix, variance/covariance of reduced form residuals.
logLik
Numeric, value of log-Likelihood.
LR
htest, LR result of over-identification test.
obs
Integer, number of observations used.
opt
List, result of optim().
iter
Integer, the count of iterations.
call
Call, the call to SVAR().
Or a list with class attribute svecsum which contains the
following elements:
type
Character, the type of SVEC-model.
SR
Matrix, contemporaneous impact matrix.
LR
Matrix, long-run impact matrix.
SRse
Matrix, standard errors for SR matrix.
LRse
Matrix, standard errors for LR matrix.
Sigma.U
Matrix, variance/covariance of reduced form residuals.
logLik
Numeric, value of log-Likelihood.
LRover
htest, LR result of over-identification test.
obs
Integer, number of observations used.
r
Integer, co-integration rank of VECM.
iter
Integer, the count of iterations.
call
Call, the call to SVEC().
Author(s)
Bernhard Pfaff
See Also
VAR, SVAR, SVEC
Examples
data(Canada)
## summary-method for varest
var.2c <- VAR(Canada, p = 2 , type = "const")
summary(var.2c)
## summary-method for svarest
amat <- diag(4)
diag(amat) <- NA
amat[2, 1] <- NA
amat[4, 1] <- NA
## Estimation method scoring
svar.a <- SVAR(x = var.2c, estmethod = "scoring", Amat = amat, Bmat = NULL,
max.iter = 100, maxls = 1000, conv.crit = 1.0e-8)
summary(svar.a)
## summary-method for svecest
vecm <- ca.jo(Canada[, c("prod", "e", "U", "rw")], type = "trace",
ecdet = "trend", K = 3, spec = "transitory")
SR <- matrix(NA, nrow = 4, ncol = 4)
SR[4, 2] <- 0
LR <- matrix(NA, nrow = 4, ncol = 4)
LR[1, 2:4] <- 0
LR[2:4, 4] <- 0
svec.b <- SVEC(vecm, LR = LR, SR = SR, r = 1, lrtest = FALSE, boot =
FALSE)
summary(svec.b)