Adaptive Sampling Designs: Inference for Sparse and Clustered Populations (SpringerBriefs in Statistics) - Softcover

Seber, George A.F. A. F.

Softcover

ISBN 10: 3642336566 ISBN 13: 9783642336560

Publisher: Springer, 2012

Synopsis

This book aims to provide an overview of some adaptive techniques used in estimating parameters for finite populations where the sampling at any stage depends on the sampling information obtained to date. The sample adapts to new information as it comes in. These methods are especially used for sparse and clustered populations.
Written by two acknowledged experts in the field of adaptive sampling.

About this title

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.

From the Back Cover

This book aims to provide an overview of some adaptive techniques used in estimating parameters for finite populations where the sampling at any stage depends on the sampling information obtained to date. The sample adapts to new information as it comes in. These methods are especially used for sparse and clustered populations.
Written by two acknowledged experts in the field of adaptive sampling.

Edition details

• Publisher: Springer
• Publication date: 2012
• Language: English
• ISBN 10: 3642336566
• ISBN 13: 9783642336560
• Binding: Paperback
• Number of pages: 79