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

G. A. F. Seber, Mohammad M. Salehi




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 | #4228662 in Books |  Springer |  2012-10-23 |  2012-10-31 | Original language:English | PDF # 1 |  9.25 x.19 x6.10l,.0 | File type: PDF | 70 pages

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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.



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