Stratification of Skewed Populations: A Comparison of Optimisation‐based versus Approximate Methods

DOI10.1111/insr.12230OpenAlexW2748169160MaRDI QIDQ6086550

M. A. Hidiroglou, Marcin Kozak

Publication date: 10 November 2023

Published in: International Statistical Review (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/insr.12230

zbMATH Keywords

numerical optimisationsample allocationcumrootf methodgeometric stratificationKozak algorithmLavallée-Hidiroglou algorithmSethi algorithm

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (5)

Revisiting sample allocation methods: a simulation-based comparison ⋮ Integrated statistical and decision models for multi-stage health care audit sampling ⋮ Heuristic algorithm for univariate stratification problem ⋮ Information‐theoretic multistage sampling framework for medical audits ⋮ Introduction to Sampling Techniques

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A genetic algorithm approach to determine stratum boundaries and sample sizes of each stratum in stratified sampling
• Model assisted survey sampling
• A comparison of approximately optimal stratification given proportional allocation with other methods of stratification and allocation
• An iterative local search approach applied to the optimal stratification problem
• Minimum Variance Stratification
• Improving the Lavallée and Hidiroglou algorithm for stratification of skewed populations
• A NOTE ON OPTIMUM STRATIFICATION OF POPULATIONS FOR ESTIMATING THE POPULATION MEANS
• Determining Optimum Strata Boundaries and Sample Sizes for Skewed Population with Log-Normal Distribution
• Stratification of Skewed Populations: A review
• An Approximation Useful in Univariate Stratification

This page was built for publication: Stratification of Skewed Populations: A Comparison of Optimisation‐based versus Approximate Methods