feglmvcov.feglm estimates the 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.
# S3 method for feglm
vcov(
object,
type = c("hessian", "outer.product", "sandwich", "clustered"),
cluster = NULL,
cluster.vars = NULL,
...
)The function vcov.feglm returns a named matrix of covariance estimates.
an object of class "feglm".
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.
a symbolic description indicating the clustering of observations.
deprecated; use cluster instead.
other arguments.
Multi-way clustering is done using the algorithm of Cameron, Gelbach, and Miller (2011). An example is provided in the vignette "Replicating an Empirical Example of International Trade".
Cameron, C., J. Gelbach, and D. Miller (2011). "Robust Inference With Multiway Clustering". Journal of Business & Economic Statistics 29(2).
feglm