fwildclusterboot

Fast Wild Cluster Bootstrap Inference for Regression Models / OLS in R. Additionally, R port to WildBootTests.jl via the JuliaConnectoR.

https://github.com/s3alfisc/fwildclusterboot

Science Score: 39.0%

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Keywords

clustered-standard-errors linear-regression-models wild-bootstrap wild-cluster-bootstrap

Last synced: 6 months ago · JSON representation

Repository

Fast Wild Cluster Bootstrap Inference for Regression Models / OLS in R. Additionally, R port to WildBootTests.jl via the JuliaConnectoR.

Basic Info

Host: GitHub
Owner: s3alfisc
License: gpl-3.0
Language: R
Default Branch: master
Homepage: https://s3alfisc.github.io/fwildclusterboot/
Size: 20.9 MB

Statistics

Stars: 25
Watchers: 2
Forks: 5
Open Issues: 30
Releases: 21

Topics

clustered-standard-errors linear-regression-models wild-bootstrap wild-cluster-bootstrap

Created almost 6 years ago · Last pushed over 1 year ago

Metadata Files

Readme Changelog Contributing License Codemeta

README.Rmd

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output: github_document
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---



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# fwildclusterboot 





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`r badger::badge_cran_download("fwildclusterboot", "last-month", "green")`



The `{fwildclusterboot}` package implements multiple fast wild cluster bootstrap algorithms as developed in [Roodman et al (2019)](https://econpapers.repec.org/paper/qedwpaper/1406.htm) and [MacKinnon, Nielsen & Webb (2022)](https://www.econ.queensu.ca/sites/econ.queensu.ca/files/wpaper/qed_wp_1485.pdf).

Via the [JuliaConnectoR](https://CRAN.R-project.org/package=JuliaConnectoR), `{fwildclusterboot}` further ports functionality of [WildBootTests.jl](https://github.com/droodman/WildBootTests.jl) - which provides an even faster implementation of the wild cluster bootstrap for OLS and supports the WRE bootstrap for IV and tests of multiple joint hypotheses.

The package's central function is `boottest()`. It allows to test univariate hypotheses using a wild cluster bootstrap at extreme speed: via the 'fast' algorithm, it is possible to run a wild cluster bootstrap with $B = 100.000$ iterations in less than a second!

```{r, fig.width=10, fig.height=3, echo = FALSE, warning = FALSE, message = FALSE}
library(ggplot2)
df <- readRDS("C:/Users/alexa/Dropbox/R package development/fwildclusterboot develop/benchmarks/r_comparions.rds")

df$B <- factor(df$B, levels = c("10K", "100K"))
df$N_G <- factor(df$N_G, levels = c("N_G = 20", "N_G = 50", "N_G = 100", "N_G = 500", "N_G = 1000"))
df$`boot algo` <- df$type
```

```{r, fig.width=10, fig.height=3, echo = FALSE, warning = FALSE, message = FALSE}
ggplot(data = df, aes(x = B, y = time, color = `boot algo`)) + 
  facet_wrap(~N_G, nrow = 1) + 
  geom_point() + 
scale_y_continuous(trans='log10') + 
  labs(title = "Benchmarks", caption = "N = 10_000, k = 20 covariates and one cluster of dimension N_G (3 iterations each, median runtime is plotted).")+
  #theme_bw() + 
  xlab("Bootstrap iterations") + 
  ylab("time in seconds, log scale") + 
  theme_bw()
```


`{fwildclusterboot}` supports the following features:

+ The wild bootstrap for OLS (Wu 1986).
+ The wild cluster bootstrap for OLS (Cameron, Gelbach & Miller 2008, Roodman et al, 2019).
+ Multiple new versions of the wild cluster bootstrap as described in MacKinnon, Nielsen & Webb (2022), including the WCR13 (WCR-V), WCR31 (WCR-S), WCR33 (WCR-B), WCU13 (WCU-V), WCU31 (WCU-S) and WCU33 (WCU-B).
+ The subcluster bootstrap (MacKinnon and Webb 2018).
+ Confidence intervals formed by inverting the test and iteratively searching for bounds.
+ Multiway clustering.
+ One-way fixed effects.

Additional features are provided through `WildBootTests.jl`:

+ Highly optimized versions of the '11' and '31' wild cluster bootstrap variants
+ A highly optimized version of the Wild Restricted Efficient bootstrap (WRE) for IV/2SLS/LIML [(Davidson & MacKinnon, 2010)](https://www.tandfonline.com/doi/abs/10.1198/jbes.2009.07221).
+ Arbitrary and multiple linear hypotheses in the parameters.

`{fwildclusterboot}` supports the following models: 

+ OLS: `lm` (from stats), `fixest` (from fixest), `felm` from (lfe)
+ IV: `ivreg` (from ivreg). 

### Installation

You can install compiled versions of`{fwildclusterboot}` from CRAN (compiled), R-universe (compiled) or github by following one of the steps below:

```{r, eval = FALSE}
# from CRAN 
install.packages("fwildclusterboot")

# from r-universe (windows & mac, compiled R > 4.0 required)
install.packages('fwildclusterboot', repos ='https://s3alfisc.r-universe.dev')
# dev version from github
# note: installation requires Rtools
library(devtools)
install_github("s3alfisc/fwildclusterboot")
```

### The `boottest()` function

For a longer introduction to `{fwildclusterboot}`, take a look at the [vignette](https://s3alfisc.github.io/fwildclusterboot/articles/fwildclusterboot.html).

```{r, warning = FALSE, message = FALSE}
library(fwildclusterboot)

# set seed via dqset.seed for engine = "R" & Rademacher, Webb & Normal weights
dqrng::dqset.seed(2352342)
# set 'familiar' seed for all other algorithms and weight types 
set.seed(23325)

data(voters)

# fit the model via fixest::feols(), lfe::felm() or stats::lm()
lm_fit <- lm(proposition_vote ~ treatment  + log_income + as.factor(Q1_immigration) + as.factor(Q2_defense), data = voters)
# bootstrap inference via boottest()
lm_boot <- boottest(lm_fit, clustid = c("group_id1"), B = 9999, param = "treatment")
summary(lm_boot)
```

## Citation 

If you are in `R`, you can simply run the following command to get the BibTeX citation for `{fwildclusterboot}`:

```{r, warning = FALSE, message = FALSE}
citation("fwildclusterboot")
```

Alternatively, if you prefer to cite the "Fast & Wild" paper by Roodman et al, it would be great if you mentioned `{fwildclusterboot}` in a footnote =) !

Owner

Name: Alexander Fischer
Login: s3alfisc
Kind: user
Location: Düsseldorf

Website: https://s3alfisc.github.io/blog/
Repositories: 7
Profile: https://github.com/s3alfisc

Data Scientist @trivago

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  "review": {
    "@type": "Review",
    "url": "https://github.com/ropensci/software-review/issues/546",
    "provider": "https://ropensci.org"
  },
  "keywords": [
    "clustered-standard-errors",
    "wild-bootstrap",
    "linear-regression-models",
    "wild-cluster-bootstrap"
  ]
}

GitHub Events

Total

Issues event: 3
Watch event: 5
Issue comment event: 9
Fork event: 1

Last Year

Issues event: 3
Watch event: 5
Issue comment event: 9
Fork event: 1

Committers

Last synced: over 2 years ago

All Time

Total Commits: 1,062
Total Committers: 4
Avg Commits per committer: 265.5
Development Distribution Score (DDS): 0.005

Past Year

Commits: 156
Committers: 3
Avg Commits per committer: 52.0
Development Distribution Score (DDS): 0.013

Top Committers

Name	Email	Commits
Alexander Fischer	a**1@t**e	1,057
droodman	d**n@g**m	3
Vincent Arel-Bundock	v**k@u**a	1
soodoku	g**7@g**m	1

Committer Domains (Top 20 + Academic)

umontreal.ca: 1 t-online.de: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time

Total issues: 102
Total pull requests: 43
Average time to close issues: about 2 months
Average time to close pull requests: 12 days
Total issue authors: 26
Total pull request authors: 4
Average comments per issue: 2.28
Average comments per pull request: 0.3
Merged pull requests: 23
Bot issues: 3
Bot pull requests: 0

Past Year

Issues: 7
Pull requests: 3
Average time to close issues: 2 days
Average time to close pull requests: 37 minutes
Issue authors: 6
Pull request authors: 1
Average comments per issue: 3.57
Average comments per pull request: 3.33
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

s3alfisc (63)
jcha1997 (4)
github-actions[bot] (3)
michaeltopper1 (3)
ccmullally (2)
etiennebacher (2)
amarbler (2)
amichuda (2)
tappek (2)
mpadge (1)
lparisi94 (1)
droodman (1)
Yuval-OS (1)
helske (1)
SebKrantz (1)

Pull Request Authors

s3alfisc (47)
vincentarelbundock (1)
soodoku (1)
tappek (1)

Top Labels

Issue Labels

enhancement (27) bug (6) documentation (3) help wanted (1) wontfix (1) can't reproduce (1)

Pull Request Labels

Packages

Total packages: 1
Total downloads:
- cran 1,167 last-month
Total docker downloads: 20,358

Total dependent packages: 1
Total dependent repositories: 1
Total versions: 16
Total maintainers: 1

cran.r-project.org: fwildclusterboot

Fast Wild Cluster Bootstrap Inference for Linear Models

Homepage: https://s3alfisc.github.io/fwildclusterboot/
Documentation: http://cran.r-project.org/web/packages/fwildclusterboot/fwildclusterboot.pdf
License: GPL-3
Status: removed
Latest release: 0.13.0
published about 3 years ago

Versions: 16
Dependent Packages: 1
Dependent Repositories: 1
Downloads: 1,167 Last month
Docker Downloads: 20,358

Rankings

Downloads: 7.5%

Docker downloads count: 12.8%

Stargazers count: 13.4%

Forks count: 14.3%

Average: 15.1%

Dependent packages count: 18.3%

Dependent repos count: 24.2%

Maintainers (1)

alexander-fischer1801@t-online.de

Last synced: 11 months ago

Dependencies

DESCRIPTION cran

Formula * imports
JuliaConnectoR * imports
Matrix * imports
Matrix.utils * imports
Rcpp * imports
collapse * imports
dqrng * imports
dreamerr * imports
generics * imports
bench * suggests
broom * suggests
clubSandwich * suggests
covr * suggests
data.table * suggests
fabricatr * suggests
fixest * suggests
ivreg * suggests
knitr * suggests
lfe * suggests
lmtest * suggests
modelsummary * suggests
rmarkdown * suggests
sandwich * suggests
testthat >= 3.0.0 suggests
tibble * suggests

.github/workflows/R-CMD-check.yaml actions

actions/cache v2 composite
actions/checkout v2 composite
actions/upload-artifact main composite
julia-actions/setup-julia v1 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite

.github/workflows/pkgdown.yaml actions

actions/checkout v2 composite
julia-actions/setup-julia v1 composite
r-lib/actions/setup-pandoc v1 composite
r-lib/actions/setup-r v1 composite
r-lib/actions/setup-r-dependencies v1 composite

.github/workflows/test-coverage.yaml actions

actions/cache v2 composite
actions/checkout v2 composite
julia-actions/setup-julia v1 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite

ecosyste.ms

Data

Tools

Indexes

Applications

Experiments

Open Source Science

fwildclusterboot

Science Score: 39.0%

Keywords

Repository

Basic Info

Statistics

Topics

Metadata Files

README.Rmd

Owner

CodeMeta (codemeta.json)

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Packages

cran.r-project.org: fwildclusterboot

Rankings

Maintainers (1)

Dependencies