gmm: vcov – R documentation

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gmm

vcov

Variance-covariance matrix of GMM or GEL

Description

It extracts the matrix of variances and covariances from gmm or gel objects.

Usage

## S3 method for class 'gmm'
vcov(object, ...)
## S3 method for class 'gel'
vcov(object, lambda = FALSE, ...)
## S3 method for class 'tsls'
vcov(object, type=c("Classical","HC0","HC1","HAC"),
                    hacProp = list(), ...)
## S3 method for class 'ategel'
vcov(object, lambda = FALSE, robToMiss = TRUE, ...)

Arguments

`object`	An object of class `gmm` or `gmm` returned by the function `gmm` or `gel`
`lambda`	If set to TRUE, the covariance matrix of the Lagrange multipliers is produced.
`type`	Type of covariance matrix for the meat
`hacProp`	A list of arguments to pass to `kernHAC`
`robToMiss`	If `TRUE`, it computes the robust to misspecification covariance matrix
`...`	Other arguments when `vcov` is applied to another class object

Details

For tsls(), if vcov is set to a different value thand "Classical", a sandwich covariance matrix is computed.

Value

A matrix of variances and covariances

Examples

# GMM #
n = 500
phi<-c(.2,.7)
thet <- 0
sd <- .2
x <- matrix(arima.sim(n = n,list(order = c(2,0,1), ar = phi, ma = thet, sd = sd)), ncol = 1)
y <- x[7:n]
ym1 <- x[6:(n-1)]
ym2 <- x[5:(n-2)]

H <- cbind(x[4:(n-3)], x[3:(n-4)], x[2:(n-5)], x[1:(n-6)])
g <- y ~ ym1 + ym2
x <- H

res <- gmm(g, x)
vcov(res)

## GEL ##

t0 <- c(0,.5,.5)
res <- gel(g, x, t0)
vcov(res)
vcov(res, lambda = TRUE)

gmm

Generalized Method of Moments and Generalized Empirical Likelihood

v1.6-6

GPL (>= 2)

Authors

Pierre Chausse <pchausse@uwaterloo.ca>

Initial release

2021-02-07