Adaptive Sampling Designs: Inference for Sparse and Clustered Populations

Adaptive Sampling Designs: Inference for Sparse and Clustered Populations

by George A.F. Seber, Mohammad M. Salehi


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Product Details

ISBN-13: 9783642336560
Publisher: Springer Berlin Heidelberg
Publication date: 10/23/2012
Series: SpringerBriefs in Statistics
Edition description: 2013
Pages: 70
Product dimensions: 6.10(w) x 9.25(h) x 0.01(d)

About the Author

George Seber is an Emeritus Professor of Statistics at Auckland University, New Zealand. He is an elected Fellow of the Royal Society of New Zealand and recipient of their Hector medal in Science. He has authored or coauthored 13 books and 77 research articles on a wide variety of topics including linear and nonlinear models, multivariate analysis, adaptive sampling, genetics, epidemiology, and statistical ecology.

Mohammad Salehi is a Professor of Statistics at Isfahan University of Technology, Iran. Currently, he is also a Professor of Statistics and Director of the Statistical Consulting Unit at Qatar University, Qatar, and has published extensively in the field of adaptive sampling.

Table of Contents

​Basic Ideas.- Adaptive Cluster Sampling.- Rao-Blackwell Modi.- Primary and Secondary Units.- Inverse Sampling Methods.- Adaptive Allocation.

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