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.]

Contributor(s):

Material type: Text

TextSeries: SpringerBriefs in StatisticsPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Description: IX, 70 p. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783642336577

Subject(s):

Additional physical formats: Printed edition:: No titleDDC classification:

519.5 23

LOC classification:

QA276-280

Online resources:

Click here to access online

Contents:

Basic Ideas -- Adaptive Cluster Sampling -- Rao-Blackwell Modi -- Primary and Secondary Units -- Inverse Sampling Methods -- Adaptive Allocation.

In: 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.

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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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