Adaptive Sampling Designs [electronic resource] :Inference for Sparse and Clustered Populations / by George A.F. Seber, Mohammad M. Salehi.
by Seber, George A.F [author.]; Salehi, Mohammad M [author.]; SpringerLink (Online service).
Material type:
BookSeries: SpringerBriefs in Statistics: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : 2013.Description: IX, 70 p. online resource.ISBN: 9783642336577.Subject(s): Statistics | Statistics | Statistics, general | Statistics for Life Sciences, Medicine, Health SciencesDDC classification: 519.5 Online resources: Click here to access online
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Springer eBooksSummary: 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.
Basic Ideas -- Adaptive Cluster Sampling -- Rao-Blackwell Modi -- Primary and Secondary Units -- Inverse Sampling Methods -- Adaptive Allocation.
| Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| MAIN LIBRARY | QA276-280 (Browse shelf) | Available |
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Basic Ideas -- Adaptive Cluster Sampling -- Rao-Blackwell Modi -- Primary and Secondary Units -- Inverse Sampling Methods -- Adaptive Allocation.
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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