Multivariate Multi-Objective Allocation in Stratified Random Sampling: A Game Theoretic Approach

We consider the problem of multivariate multi-objective allocation where no or limited information is available within the stratum variance. Results show that a game theoretic approach (based on weighted goal programming) can be applied to sample size allocation problems. We use simulation technique...

Descripción completa

Detalles Bibliográficos
Autores principales: Muhammad, Yousaf Shad, Hussain, Ijaz, Shoukry, Alaa Mohamd
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5147966/
https://www.ncbi.nlm.nih.gov/pubmed/27936039
http://dx.doi.org/10.1371/journal.pone.0167705
_version_ 1782473771426250752
author Muhammad, Yousaf Shad
Hussain, Ijaz
Shoukry, Alaa Mohamd
author_facet Muhammad, Yousaf Shad
Hussain, Ijaz
Shoukry, Alaa Mohamd
author_sort Muhammad, Yousaf Shad
collection PubMed
description We consider the problem of multivariate multi-objective allocation where no or limited information is available within the stratum variance. Results show that a game theoretic approach (based on weighted goal programming) can be applied to sample size allocation problems. We use simulation technique to determine payoff matrix and to solve a minimax game.
format Online
Article
Text
id pubmed-5147966
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-51479662016-12-28 Multivariate Multi-Objective Allocation in Stratified Random Sampling: A Game Theoretic Approach Muhammad, Yousaf Shad Hussain, Ijaz Shoukry, Alaa Mohamd PLoS One Research Article We consider the problem of multivariate multi-objective allocation where no or limited information is available within the stratum variance. Results show that a game theoretic approach (based on weighted goal programming) can be applied to sample size allocation problems. We use simulation technique to determine payoff matrix and to solve a minimax game. Public Library of Science 2016-12-09 /pmc/articles/PMC5147966/ /pubmed/27936039 http://dx.doi.org/10.1371/journal.pone.0167705 Text en © 2016 Muhammad et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Muhammad, Yousaf Shad
Hussain, Ijaz
Shoukry, Alaa Mohamd
Multivariate Multi-Objective Allocation in Stratified Random Sampling: A Game Theoretic Approach
title Multivariate Multi-Objective Allocation in Stratified Random Sampling: A Game Theoretic Approach
title_full Multivariate Multi-Objective Allocation in Stratified Random Sampling: A Game Theoretic Approach
title_fullStr Multivariate Multi-Objective Allocation in Stratified Random Sampling: A Game Theoretic Approach
title_full_unstemmed Multivariate Multi-Objective Allocation in Stratified Random Sampling: A Game Theoretic Approach
title_short Multivariate Multi-Objective Allocation in Stratified Random Sampling: A Game Theoretic Approach
title_sort multivariate multi-objective allocation in stratified random sampling: a game theoretic approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5147966/
https://www.ncbi.nlm.nih.gov/pubmed/27936039
http://dx.doi.org/10.1371/journal.pone.0167705
work_keys_str_mv AT muhammadyousafshad multivariatemultiobjectiveallocationinstratifiedrandomsamplingagametheoreticapproach
AT hussainijaz multivariatemultiobjectiveallocationinstratifiedrandomsamplingagametheoreticapproach
AT shoukryalaamohamd multivariatemultiobjectiveallocationinstratifiedrandomsamplingagametheoreticapproach

Ejemplares similares