# vcov: Variance-covariance matrix of GMM or GEL In gmm: Generalized Method of Moments and Generalized Empirical Likelihood

## Description

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

## Usage

 ```1 2 3 4 5 6 7 8 9``` ```## 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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23``` ```# 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 documentation built on March 18, 2018, 2:30 p.m.