piktfrompik

This function finds the <code>pikt</code> from an initial <code>pik</code>.

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

piktfrompik function

<dl><dt>pik</dt>
<dd>A vector of inclusion probabilities. The vector must contains only value that are not integer.</dd>
<dt>max_iter</dt>
<dd>An integer that specify the maximum iteration in the Newton-Raphson algorithm. Default <code>500</code>.</dd>
<dt>tol</dt>
<dd>A scalar that specify the tolerance convergence for the Newton-Raphson algorithm. Default <code>1e-8</code>.</dd></dl>

Arguments

Raphaël Jauslin <a href="/link/raphael.jauslin%40unine.ch?package=StratifiedSampling&version=0.4.1" data-mini-rdoc="StratifiedSampling::raphael.jauslin@unine.ch">raphael.jauslin@unine.ch</a>

Author

pikt from pik — piktfrompik

<dl>

<dt>pik</dt>
<dd>A vector of inclusion probabilities. The vector must contains only value that are not integer.</dd>


<dt>max_iter</dt>
<dd>An integer that specify the maximum iteration in the Newton-Raphson algorithm. Default <code>500</code>.</dd>


<dt>tol</dt>
<dd>A scalar that specify the tolerance convergence for the Newton-Raphson algorithm. Default <code>1e-8</code>.</dd>

</dl>

Raphaël Jauslin <a href='mailto:raphael.jauslin@unine.ch'>raphael.jauslin@unine.ch</a>

piktfrompik: pikt from pik

Description

Usage

Value

Arguments

Author

Details

References