Adaptive Sampling Designs : Inference for Sparse and Clustered Populations / by George A.F. Seber, Mohammad M. Salehi.
Tipo de material:
TextoSeries SpringerBriefs in StatisticsEditor: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Descripción: Ix, 70 páginas recurso en líneaTipo de contenido: - texto
- computadora
- recurso en línea
- 9783642336577
- QA276-280
Contenidos:
Resumen: 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.
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Springer eBooks
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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