Covariance matrix for the estimator of the structural parameters
from objects returned by feglm. The covariance is computed
from the hessian, the scores, or a combination of both after convergence.
Usage
# S3 method for feglm
vcov(
object,
type = c("hessian", "outer.product", "sandwich", "clustered"),
...
)
Value
A named matrix of covariance estimates.
A named matrix of covariance estimates.
Arguments
object
an object of class "feglm".
type
the type of covariance estimate required. "hessian" refers
to the inverse of the negative expected hessian after convergence and is the
default option. "outer.product" is the outer-product-of-the-gradient
estimator. "sandwich" is the sandwich estimator (sometimes also
referred as robust estimator), and "clustered" computes a clustered
covariance matrix given some cluster variables.
...
additional arguments.
References
Cameron, C., J. Gelbach, and D. Miller (2011). "Robust Inference
With Multiway Clustering". Journal of Business & Economic Statistics 29(2).
# same as the example in feglm but extracting the covariance matrixmod <- fepoisson(mpg ~ wt | cyl | am, mtcars)
round(vcov(mod, type = "clustered"), 5)