maxentpi2

This function computes the matrix of the joint inclusion of the maximum entropy sampling with fixed sample size. It can handle unequal inclusion probabilities.

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 <doi:10.1016/j.jspi.2022.12.003>.

Raphael Jauslin

StratifiedSampling

Different Methods for Stratified Sampling

Esther Eustache

Bardia Panahbehagh

Yves Tillé

maxentpi2 function

<dl><dt>pikr</dt>
<dd>A vector of inclusion probabilities.</dd></dl>

Arguments

Joint inclusion probabilities of maximum entropy. — maxentpi2

<dl>

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

</dl>

maxentpi2: Joint inclusion probabilities of maximum entropy.

Description

Usage

Value

Arguments

Details

References