bbw0.3.1 package

Blocked Weighted Bootstrap

bbw

Blocked Weighted Bootstrap

boot_bw_estimate

Estimate median and confidence intervals from bootstrap replicates

boot_bw

Blocked Weighted Bootstrap - vectorised and parallel

boot_percentile

Boot estimate

bootBW

Blocked Weighted Bootstrap

bootClassic

Simple proportion statistics function for bootstrap estimation

bootPROBIT

PROBIT statistics function for bootstrap estimation

calc_total_ci

Calculate confidence limits

calc_total_estimate

Calculate total estimate

calc_total_sd

Calculate total sd

check_data

Check data

check_est_df

Check est_df

check_params

Check variables

check_pop_df

Check pop_df

estimate_total_

Estimate post-stratification weighted totals

estimate_total

Post-stratification analysis

get_strata

Get levels of stratification

recode

Recode

tidy_boot

Tidy bootstraps

Download source packageRead PDF manual

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.

  • Maintainer: Ernest Guevarra
  • License: GPL-3
  • Last published: 2026-01-21

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