Package: bbw 0.3.1.9000

Ernest Guevarra

bbw: Blocked Weighted Bootstrap

The blocked weighted bootstrap (BBW) is an estimation technique for use with data from two-stage cluster sampled surveys in which either prior weighting (e.g. population-proportional sampling or PPS as used in Standardized Monitoring and Assessment of Relief and Transitions or SMART surveys) or posterior weighting (e.g. as used in rapid assessment method or RAM and simple spatial sampling method or S3M surveys) is implemented. See Cameron et al (2008) <doi:10.1162/rest.90.3.414> for application of bootstrap to cluster samples. See Aaron et al (2016) <doi:10.1371/journal.pone.0163176> and Aaron et al (2016) <doi:10.1371/journal.pone.0162462> for application of the blocked weighted bootstrap to estimate indicators from two-stage cluster sampled surveys.

Authors:Mark Myatt [aut, cph], Ernest Guevarra [aut, cre, cph]

bbw_0.3.1.9000.tar.gz
bbw_0.3.1.9000.zip(r-4.7)bbw_0.3.1.9000.zip(r-4.6)bbw_0.3.1.9000.zip(r-4.5)
bbw_0.3.1.9000.tgz(r-4.6-any)bbw_0.3.1.9000.tgz(r-4.5-any)
bbw_0.3.1.9000.tar.gz(r-4.7-any)bbw_0.3.1.9000.tar.gz(r-4.6-any)
bbw_0.3.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bbw/json (API)

# Install 'bbw' in R:
install.packages('bbw', repos = c('https://rapidsurveys.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/rapidsurveys/bbw/issues

Pkgdown/docs site:https://rapidsurveys.io

Datasets:

On CRAN:

Conda:

bootstrapping-statisticsramsurveys

5.13 score 3 stars 1 packages 9 scripts 312 downloads 12 exports 74 dependencies

Last updated from:b9abe7aac1. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK190
source / vignettesOK195
linux-release-x86_64OK177
macos-release-arm64OK174
macos-oldrel-arm64OK148
windows-develOK151
windows-releaseOK138
windows-oldrelOK123
wasm-releaseOK136

Exports:boot_bwboot_bw_estimateboot_bw_parallelboot_bw_sample_clustersboot_bw_sample_within_clustersboot_bw_sequentialboot_bw_weightbootBWbootClassicbootPROBITestimate_totalrecode

Dependencies:abindbackportsbootbroomcarcarDataclicodetoolscolorspacecowplotcpp11DerivdoBydoParalleldplyrfarverforeachforecastFormulafracdiffgenericsggplot2gluegtableisobanditeratorslabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrnlmenloptrnnetnumDerivparallellypbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

Blocked Weighted Bootstrap
Features of blocked weighted bootstrap | Posterior weighting through resampling | Development history | Advantages
Rendered frombbw.Rmdusingknitr::rmarkdown

Last update: 2026-01-20
Started: 2018-01-14

Using bbw with parallel computation
Bootstrap resampling without parallelisation | Using one parameter and 400 replicates | Using varying number of parameters and 400 replicates | Bootstrap resampling with parallelisation
Rendered frombbw-parallel.Rmdusingknitr::rmarkdown

Last update: 2025-01-15
Started: 2025-01-15

Blocked weighted bootstrap estimation
Original bootstrapping workflow | Bootstrap resampling with bootBW() | Bootstrap estimation | Stratified bootstrap resampling | Alternative blocked weighted bootstrap function set | Bootstrap resampling with boot_bw()
Rendered frombbw-estimation.Rmdusingknitr::rmarkdown

Last update: 2025-01-11
Started: 2025-01-08