summary: Summary method for objects of class varest, svarest and...

In vars: VAR Modelling

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) 

vars documentation built on June 24, 2024, 9:08 a.m.