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Algorithms for response adaptive sampling designs
Author(s) -
Hardwick Janis,
Stout Quentin F.
Publication year - 2009
Publication title -
wiley interdisciplinary reviews: computational statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 38
eISSN - 1939-0068
pISSN - 1939-5108
DOI - 10.1002/wics.25
Subject(s) - sampling (signal processing) , computer science , adaptive sampling , sample (material) , sampling design , sample size determination , order (exchange) , algorithm , mathematical optimization , statistics , mathematics , monte carlo method , population , chemistry , demography , filter (signal processing) , chromatography , finance , sociology , economics , computer vision
An experimental design is a formula or algorithm that specifies how resources are to be utilized throughout a study. The design is considered to be good or even optimal if it allows for sufficiently precise and accurate data analysis with the least output of resources such as time, money and experimental units. Most experimental designs use fixed sampling procedures in which the sample sizes and order of allocations to different study groups are known in advance. Copyright © 2009 John Wiley & Sons, Inc. This article is categorized under: Statistical and Graphical Methods of Data Analysis > Sampling