summary.feglm: Summarizing models of class 'feglm'

In alpaca: Fit GLM's with High-Dimensional k-Way Fixed Effects

Summarizing models of class feglm

Description

Summary statistics for objects of class "feglm".

Usage

## S3 method for class 'feglm'
summary(
  object,
  type = c("hessian", "outer.product", "sandwich", "clustered"),
  cluster = NULL,
  cluster.vars = NULL,
  ...
)

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 refered as robust estimator), and "clustered" computes a clustered covariance matrix given some cluster variables.
cluster	a symbolic description indicating the clustering of observations.
cluster.vars	deprecated; use cluster instead.
...	other arguments.

Details

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".

Value

Returns an object of class "summary.feglm" which is a list of summary statistics of object.

References

Cameron, C., J. Gelbach, and D. Miller (2011). "Robust Inference With Multiway Clustering". Journal of Business & Economic Statistics 29(2).

See Also

feglm

alpaca documentation built on Aug. 10, 2022, 5:08 p.m.