title: Multivariate Multi-Objective Allocation in Stratified Random Sampling: A Game Theoretic Approach.
abstract: 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.
authors.affiliation: Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan.
authors.forename: Yousaf Shad
authors.identifier: http://orcid.org/0000-0002-3541-6220
authors.initials: YS
authors.lastname: Muhammad
authors.affiliation: Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan.
authors.forename: Ijaz
authors.initials: I
authors.lastname: Hussain
authors.affiliation: Arriyadh Community College, King Saud University Riyadh Saudi Arabia; King Saud University, KSA workers University, Egypt.
authors.forename: Alaa Mohamd
authors.initials: AM
authors.lastname: Shoukry
mesh_terms: D000465:Algorithms; D000818:Animals; D005716:Game Theory; D006801:Humans; D015999:Multivariate Analysis; D011156:Population Density; D011897:Random Allocation; D018401:Sample Size