balseq

Selects at the same time a well-spread and a balanced sample using a sequential implementation.

Integrating a stratified structure in the population in a sampling design can considerably reduce the variance of the Horvitz-Thompson estimator. We propose in this package different methods to handle the selection of a balanced sample in stratified population. For more details see Raphaël Jauslin, Esther Eustache and Yves Tillé (2021) <doi:10.1007/s42081-021-00134-y>. The package propose also a method based on optimal transport and balanced sampling, see Raphaël Jauslin and Yves Tillé <arXiv:2105.08379>.

Rapha<c3><ab>l Jauslin

StratifiedSampling

Different Methods for Stratified Sampling

Raphael Jauslin

Esther Eustache

Bardia Panahbehagh

Yves Tillé

balseq function

<dl><dt>pik</dt>
<dd>A vector of inclusion probabilities.</dd>
<dt>Xaux</dt>
<dd>A matrix of auxiliary variables. The matrix must contains the <code>pik</code> vector to have fixed sample size.</dd>
<dt>Xspread</dt>
<dd>An optional matrix of spatial coordinates.</dd>
<dt>rord</dt>
<dd>A logical variable that specify if reordering is applied. Default TRUE.</dd></dl>

Arguments

Sequential balanced sampling — balseq

<dl>

<dt>pik</dt>
<dd>A vector of inclusion probabilities.</dd>


<dt>Xaux</dt>
<dd>A matrix of auxiliary variables. The matrix must contains the <code>pik</code> vector to have fixed sample size.</dd>


<dt>Xspread</dt>
<dd>An optional matrix of spatial coordinates.</dd>


<dt>rord</dt>
<dd>A logical variable that specify if reordering is applied. Default TRUE.</dd>

</dl>

balseq: Sequential balanced sampling

Description

Usage

Value

Arguments

Details

See Also

Examples