rds.mc.boot.draws

This algorithm picks a respondent from the survey
to be a seed uniformly at random. it then generates
a bootstrap draw by simulating the markov process
forward for n steps, where n is the size of the draw
required.
If you wish the bootstrap dataset to end up with
variables from the original dataset other than the
traits and degree, then you must specify this when
you construct <code>dd</code> using the
'<code>estimate.degree.distns</code> function.

Implements different kinds of bootstraps
to estimate sampling variation from survey data with
complex designs. Includes the rescaled bootstrap
described in Rust and Rao (1996) <doi:10.1177/096228029600500305> and
Rao and Wu (1988) <doi:10.1080/01621459.1988.10478591>.

Dennis M Feehan

surveybootstrap

Bootstrap with Survey Data

rds.mc.boot.draws function

<dl><dt>chains</dt>
<dd>A list with the chains constructed from the survey
using <code>make.chain</code></dd>
<dt>mm</dt>
<dd>The mixing model</dd>
<dt>dd</dt>
<dd>The degree distributions</dd>
<dt>num.reps</dt>
<dd>The number of bootstrap resamples we want</dd></dl>

Arguments

Draw RDS bootstrap resamples using the
algorithm in Salganik 2006 (see Details below) — rds.mc.boot.draws

<dl>

<dt>chains</dt>
<dd>A list with the chains constructed from the survey
using <code>make.chain</code></dd>


<dt>mm</dt>
<dd>The mixing model</dd>


<dt>dd</dt>
<dd>The degree distributions</dd>


<dt>num.reps</dt>
<dd>The number of bootstrap resamples we want</dd>

</dl>

rds.mc.boot.draws: Draw RDS bootstrap resamples using the algorithm in Salganik 2006 (see Details below)

Description

Usage

Value

Arguments

Details