boot_bw_estimate

Estimate median and confidence intervals from bootstrap replicates

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.

Ernest Guevarra

Blocked Weighted Bootstrap

Mark Myatt

boot_bw_estimate function

<dl><dt>boot_df</dt>
<dd>A <code><a href="/link/data.frame()?package=bbw&version=0.3.1" data-mini-rdoc="bbw::data.frame()">data.frame()</a></code> or a list of <code><a href="/link/data.frame()?package=bbw&version=0.3.1" data-mini-rdoc="bbw::data.frame()">data.frame()</a></code>s of bootstrap
replicates with columns for each indicator to estimate. This is produced
by a call to <code>boot_bw()</code>.</dd></dl>

Arguments

Estimate median and confidence intervals from bootstrap replicates — boot_bw_estimate

<dl>

<dt>boot_df</dt>
<dd>A <code><a href='https://rdrr.io/r/base/data.frame.html'>data.frame()</a></code> or a list of <code><a href='https://rdrr.io/r/base/data.frame.html'>data.frame()</a></code>s of bootstrap
replicates with columns for each indicator to estimate. This is produced
by a call to <code>boot_bw()</code>.</dd>

</dl>

boot_bw_estimate: Estimate median and confidence intervals from bootstrap replicates

Description

Usage

Value

Arguments

Examples