Description

Book Synopsis
Combining the two statistical techniques of network sampling and adaptive sampling, this book illustrates the advantages of using them in tandem to effectively capture sparsely located elements in unknown pockets. It shows how network sampling is a reliable guide in capturing inaccessible entities through linked auxiliaries. The text also explores how adaptive sampling is strengthened in information content through subsidiary sampling with devices to mitigate unmanageable expanding sample sizes. Empirical data illustrates the applicability of both methods.

Table of Contents
Introduction. Certain Common Methods of Sampling Finite Populations and Estimation Procedures: Prerequisite for Network and Adaptive Sampling. A Plea for Network Sampling: Theory and Applications. Need for Adaptive Sampling: Relevant Theory of Unbiased Estimator. Adaptive and Network Sampling in Tandem. Applications and Case Studies.

Network and Adaptive Sampling

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    A Hardback by Arijit Chaudhuri

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      Publisher: Taylor & Francis Inc
      Publication Date: Publication Date: 20/08/2014
      ISBN13: 9781466577565, 978-1466577565
      ISBN10: 1466577568

      Description

      Book Synopsis
      Combining the two statistical techniques of network sampling and adaptive sampling, this book illustrates the advantages of using them in tandem to effectively capture sparsely located elements in unknown pockets. It shows how network sampling is a reliable guide in capturing inaccessible entities through linked auxiliaries. The text also explores how adaptive sampling is strengthened in information content through subsidiary sampling with devices to mitigate unmanageable expanding sample sizes. Empirical data illustrates the applicability of both methods.

      Table of Contents
      Introduction. Certain Common Methods of Sampling Finite Populations and Estimation Procedures: Prerequisite for Network and Adaptive Sampling. A Plea for Network Sampling: Theory and Applications. Need for Adaptive Sampling: Relevant Theory of Unbiased Estimator. Adaptive and Network Sampling in Tandem. Applications and Case Studies.

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