Stratified probability-proportional-to-size (PPS) sampling using permanent random numbers. Can also be used for non-stratified PPS using a dummy stratum taking the same value for each object.

Survey sampling using permanent random numbers (PRN's). A solution to the
problem of unknown overlap between survey samples, which leads to a low
precision in estimates when the survey is repeated or combined with other
surveys. The PRN solution is to supply the U(0, 1) random numbers to the
sampling procedure, instead of having the sampling procedure generate them.
In Lindblom (2014) <doi:10.2478/jos-2014-0047>, and therein cited articles,
it is shown how this is carried out and how it improves the estimates. This
package supports two common fixed-size sampling procedures (simple random
sampling and probability-proportional-to-size sampling) and includes a
function for transforming the PRN's in order to control the sample overlap.

Kira Gylling

prnsamplr

Permanent Random Number Sampling

pps function

<dl> <dt>df</dt>
<dd>Data frame containing the elements to sample from.</dd> <dt>stratid</dt>
<dd>Variable in <code>df</code> containing the strata.</dd> <dt>nsamp</dt>
<dd>Variable in <code>df</code> containing the sample sizes.</dd> <dt>prn</dt>
<dd>Variable in <code>df</code> containing the permanent random numbers.</dd> <dt>size</dt>
<dd>Variable in <code>df</code> containing the size measure.</dd></dl>

Arguments

Stratified probability-proportional-to-size sampling — pps

<dl>

 <dt>df</dt>
<dd>Data frame containing the elements to sample from.</dd>

 <dt>stratid</dt>
<dd>Variable in <code>df</code> containing the strata.</dd>

 <dt>nsamp</dt>
<dd>Variable in <code>df</code> containing the sample sizes.</dd>

 <dt>prn</dt>
<dd>Variable in <code>df</code> containing the permanent random numbers.</dd>

 <dt>size</dt>
<dd>Variable in <code>df</code> containing the size measure.</dd>

</dl>

pps: Stratified probability-proportional-to-size sampling

Description

Usage

Value

Arguments

See Also

Examples