Stochastic optimal design in multivariate stratified sampling

This work considers the allocation problem for multivariate stratified random sampling as a problem of integer non-linear stochastic multiobjective mathematical programming. With this goal in mind the asymptotic distribution of the vector of sample variances is studied. Two alternative approaches ar...

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Bibliographic Details
Published in:Optimization Vol. 63; no. 11; pp. 1665 - 1688
Main Authors: Díaz-García, José A., Ramos-Quiroga, Rogelio
Format: Journal Article
Language:English
Published: Philadelphia Routledge 01.11.2014
Taylor & Francis LLC
Subjects:
Allocations
Asymptotic methods
Asymptotic properties
Design optimization
goal programming
Integer programming
Mathematical analysis
Mathematical problems
Mathematical programming
multiobjective E-model
multiobjective P-model
multiobjective V-model
multivariate stratified random sampling
Optimization
optimum allocation
Random number sampling
Random sampling
Sampling
Stochastic models
stochastic multiobjective programming
Stochasticity
Studies
Vectors (mathematics)
ISSN:0233-1934, 1029-4945
Online Access:Get full text
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Summary:This work considers the allocation problem for multivariate stratified random sampling as a problem of integer non-linear stochastic multiobjective mathematical programming. With this goal in mind the asymptotic distribution of the vector of sample variances is studied. Two alternative approaches are suggested for solving the allocation problem for multivariate stratified random sampling. An example is presented by applying the different proposed techniques.
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ISSN:0233-1934
1029-4945
DOI:10.1080/02331934.2012.728218