Adaptive Sampling Designs [electronic resource] : 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 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642336577Trabajos contenidos: SpringerLink (Online service)Tema(s): Statistics | Statistics | Statistics, general | Statistics for Life Sciences, Medicine, Health SciencesFormatos físicos adicionales: Sin títuloClasificación CDD: 519.5 Clasificación LoC:QA276-280Recursos en línea: de clik aquí para ver el libro electrónico
Contenidos:
Springer eBooksResumen: 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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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.
ZDB-2-SMA
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