summary.boottest

object

digits

<p>Further arguments passed to or from other methods.</p>

<p>S3 method to summarize objects of class boottest</p>

Implementation of the fast algorithm for wild cluster bootstrap
inference developed in Roodman et al (2019, STATA Journal) for
linear regression models
<https://journals.sagepub.com/doi/full/10.1177/1536867X19830877>,
which makes it feasible to quickly calculate bootstrap test
statistics based on a large number of bootstrap draws even for
large samples - as long as the number of bootstrapping clusters
is not too large. Multiway clustering, regression weights,
bootstrap weights, fixed effects and subcluster bootstrapping
are supported. Further, both restricted (WCR) and unrestricted
(WCU) bootstrap are supported. Methods are provided for a variety
of fitted models, including 'lm()', 'feols()'
(from package 'fixest') and 'felm()' (from package 'lfe').

Alexander Fischer

fwildclusterboot

Fast Wild Cluster Bootstrap Inference for Linear Regression
Models

David Roodman

Achim Zeileis

Nathaniel Graham

Susanne Koell

Laurent Berge

Sebastian Krantz

summary.boottest function

S3 method to summarize objects of class boottest — summary.boottest

S3 method to summarize objects of class boottest

summary.boottest: S3 method to summarize objects of class boottest

Description

Usage

Arguments

Value