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Offering a viable solution to the long-standing problem of estimating the abundance of rare, clustered populations, adaptive sampling designs are rapidly gaining prominence in the natural and social sciences as well as in other fields with inherently difficult sampling situations. In marked contrast to conventional sampling designs, in which the entire sample of units to be observed is fixed prior to the survey, adaptive sampling strategies allow for increased sampling intensity depending upon observations made during the survey. For example, in a survey to assess the abundance of a rare animal species, neighboring sites may be added to the sample whenever the species is encountered during the survey. In an epidemiological survey of a contagious or genetically linked disease, sampling intensity may be increased whenever prevalence of the disease is encountered.
Written by two acknowledged experts in this emerging field, this book offers researchers their first comprehensive introduction to adaptive sampling. An ideal reference for statisticians conducting research in survey designs and spatial statistics as well as researchers working in the environmental, ecological, public health, and biomedical sciences.
Adaptive Sampling:
* Provides a comprehensive, fully integrated introduction to adaptive sampling theory and practice
* Describes recent research findings
* Introduces readers to a wide range of adaptive sampling strategies and techniques
* Includes numerous real-world examples from environmental pollution studies, surveys of rare animal and plant species, studies of contagious diseases, marketing surveys, mineral and fossil-fuel assessments, and more
- Sales Rank: #2623598 in Books
- Published on: 1996-05-24
- Original language: English
- Number of items: 1
- Dimensions: 9.53" h x .79" w x 6.46" l, 1.24 pounds
- Binding: Hardcover
- 288 pages
From the Publisher
This new field has attracted a high level of interest lately due to the remarkable efficiency gain possible for some types of population. Leading researchers in this area offer a cutting-edge, comprehensive look at adaptive sampling designs in which the procedure for selecting the units to include in the sample may depend on observations made during the survey. These strategies provide a solution for the long-standing problem of estimating the abundance of rare, clustered populations.
From the Back Cover
Offering a viable solution to the long-standing problem of estimating the abundance of rare, clustered populations, adaptive sampling designs are rapidly gaining prominence in the natural and social sciences as well as in other fields with inherently difficult sampling situations. In marked contrast to conventional sampling designs, in which the entire sample of units to be observed is fixed prior to the survey, adaptive sampling strategies allow for increased sampling intensity depending upon observations made during the survey. For example, in a survey to assess the abundance of a rare animal species, neighboring sites may be added to the sample whenever the species is encountered during the survey. In an epidemiological survey of a contagious or genetically linked disease, sampling intensity may be increased whenever prevalence of the disease is encountered.
Written by two acknowledged experts in this emerging field, this book offers researchers their first comprehensive introduction to adaptive sampling. An ideal reference for statisticians conducting research in survey designs and spatial statistics as well as researchers working in the environmental, ecological, public health, and biomedical sciences.
Adaptive Sampling:
- Provides a comprehensive, fully integrated introduction to adaptive sampling theory and practice
- Describes recent research findings
- Introduces readers to a wide range of adaptive sampling strategies and techniques
- Includes numerous real-world examples from environmental pollution studies, surveys of rare animal and plant species, studies of contagious diseases, marketing surveys, mineral and fossil-fuel assessments, and more
About the Author
STEVEN K. THOMPSON, PhD, is a professor in the Department of Statistics at Pennsylvania State University.
GEORGE A. F. SEBER, PhD, is a professor in the Department of Statistics at the University of Auckland, New Zealand.
Most helpful customer reviews
7 of 10 people found the following review helpful.
A nice mix of theory and examples for sampling of rare pops.
By A Customer
This is a fantastic book on advanced sampling techniques of rare, clustered, populations. The reader should be familiar with basic cluster sampling methodology. The authors develop the theory behind the techniques, and illustrate the methodoly with good, insightful examples.
0 of 0 people found the following review helpful.
Interesting, but perhaps you should just read the paper.
By Kyle Wilshusen
A fine book, but does not add that much upon Serber and Thompson's papers on the subject.
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