Optimal stratification and grouping by dynamic programming

DOI10.1007/BF01899725zbMath0321.62012MaRDI QIDQ1223100

K. Appert

Publication date: 1975

Published in: Metrika (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/175668

Mathematics Subject Classification ID

Sampling theory, sample surveys (62D05) Hamilton-Jacobi theories (49L99)

Related Items (12)

Fast balanced sampling for highly stratified population ⋮ A comparative study of some discrete descent approaches in stratified sampling ⋮ Unnamed Item ⋮ stratifyR: An R Package for optimal stratification and sample allocation for univariate populations ⋮ Ein Verfahrensvorschlag für die permanente Stichprobeninventur ⋮ Equilibrated strategy for population variance estimation ⋮ Optimal estimation of population variance using equilibrated stratified sampling from infinite populations ⋮ Designing stratified sampling in economic and business surveys ⋮ Determining the optimum stratum boundaries using mathematical programming ⋮ An efficient two-stage heuristic stratification and Neyman-allocation procedure ⋮ Determining Optimum Strata Boundaries and Sample Sizes for Skewed Population with Log-Normal Distribution ⋮ Optimal stratification in stratified designs using weibull-distributed auxiliary information

Cites Work

• Unnamed Item
• On Grouping for Maximum Homogeneity
• Minimum Variance Stratification
• Note on Grouping
• A NOTE ON OPTIMUM STRATIFICATION OF POPULATIONS FOR ESTIMATING THE POPULATION MEANS
• Zur existenz optimaler schichtungen
• A Graphical Solution for the Determination of an Optimal Stratification or Grouping, with an Example concerning a Problem of Maximizing Sales Revenues
• Optimierung in der Stichprobentheorie durch Schichtung und Aufteilung
• Die verwendung eines iterativen analogrechners zur bestimmung der gesamten lösungsmenge der dalenius-gleichungen (für verschiedene aufteilungsarten) bei kleinen schichtanzahlen¹
• Die zeichnerische Ermittlung der besten Schichtung einer Gesamtheit (bei proportionaler Aufteilung der Probe) mit Hilfe der Lorenzkurve

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