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

summary {vars} | 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)

[Package vars version 1.5-3 Index]