Package: fwildclusterboot
Title: Fast Wild Cluster Bootstrap Inference for Linear Models
Version: 0.13.0
Authors@R: 
    c(
    person(given = "Alexander",
           family = "Fischer",
           role = c("aut", "cre"),
           email = "alexander-fischer1801@t-online.de"),
    person(given = "David", 
           family = "Roodman", 
           role = "aut"), 
    person(given = "Achim", 
           family = "Zeileis",
           role = c("ctb"),
           comment = "Author of included sandwich fragments"),
	person(given = "Nathaniel",
	       family = "Graham",
	       role = c("ctb"), 
           comment = "Contributor to included sandwich fragments"),
	person(given = "Susanne",
	       family = "Koell", 
	       role = c("ctb"), 
           comment = "Contributor to included sandwich fragments"),
	person("Laurent", 
	        "Berge",
	        role = c("ctb"), 
            comment = "Author of included fixest fragments"),
	 person("Sebastian", 
	        "Krantz", 
	         role = c("ctb"))
	)
Description: Implementation of fast algorithms for wild cluster bootstrap 
             inference developed in 'Roodman et al' (2019, 'STATA' Journal,
             <doi:10.1177/1536867X19830877>) and 'MacKinnon et al' (2022), 
             which makes it feasible to quickly calculate bootstrap test 
             statistics based on a large number of bootstrap draws even for 
             large samples. Multiple bootstrap types as described in 'MacKinnon, 
             Nielsen & Webb' (2022) are supported. 
             Further, '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'). 
             Additionally implements a 'heteroskedasticity-robust' ('HC1') wild 
             bootstrap.
             Last, the package provides an R binding to 'WildBootTests.jl',
             which provides additional speed gains and functionality, 
             including the 'WRE' bootstrap for instrumental variable models 
             (based on models of type 'ivreg()' from package 'ivreg')
             and hypotheses with q > 1.
URL: https://s3alfisc.github.io/fwildclusterboot/
BugReports: https://github.com/s3alfisc/fwildclusterboot/issues/
License: GPL-3
Imports: collapse, dreamerr, Formula, generics, dqrng, gtools, Matrix,
        JuliaConnectoR, MASS, Rcpp, summclust, rlang
Suggests: fixest, lfe, ivreg, clubSandwich, lmtest, data.table,
        fabricatr, covr, knitr, rmarkdown, broom, modelsummary, bench,
        testthat (>= 3.0.0), tibble, sandwich
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.1
LinkingTo: Rcpp,RcppArmadillo, RcppEigen
VignetteBuilder: knitr
Language: en-US
SystemRequirements: Version Requirements to run the wild bootstrap
        through Julia - Julia (>= 1.8), WildBootTests.jl (>=0.9). Julia
        is downloadable via the official Julia website
        (https://julialang.org/downloads/), WildBootTests.jl via
        Julia's package manager
        (https://docs.julialang.org/en/v1/stdlib/Pkg/) or its github
        repository (https://github.com/droodman/WildBootTests.jl)
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2023-02-25 15:11:24 UTC; alexa
Author: Alexander Fischer [aut, cre],
  David Roodman [aut],
  Achim Zeileis [ctb] (Author of included sandwich fragments),
  Nathaniel Graham [ctb] (Contributor to included sandwich fragments),
  Susanne Koell [ctb] (Contributor to included sandwich fragments),
  Laurent Berge [ctb] (Author of included fixest fragments),
  Sebastian Krantz [ctb]
Maintainer: Alexander Fischer <alexander-fischer1801@t-online.de>
Repository: CRAN
Date/Publication: 2023-02-26 01:00:13 UTC
Built: R 4.2.3; x86_64-w64-mingw32; 2024-04-24 01:29:38 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
