Adaptive Sampling: 231 (Wiley Series in Probability and Statistics) - Hardcover

Thompson; Seber

Hardcover

ISBN 10: 0471558710 ISBN 13: 9780471558712

Verlag: John Wiley & Sons, 1996

Inhaltsangabe

Offering a viable solution to the long-standing problem ofestimating the abundance of rare, clustered populations, adaptivesampling designs are rapidly gaining prominence in the natural andsocial sciences as well as in other fields with inherentlydifficult sampling situations. In marked contrast to conventionalsampling designs, in which the entire sample of units to beobserved is fixed prior to the survey, adaptive sampling strategiesallow for increased sampling intensity depending upon observationsmade during the survey. For example, in a survey to assess theabundance of a rare animal species, neighboring sites may be addedto the sample whenever the species is encountered during thesurvey. In an epidemiological survey of a contagious or geneticallylinked disease, sampling intensity may be increased wheneverprevalence of the disease is encountered.

Written by two acknowledged experts in this emerging field, thisbook offers researchers their first comprehensive introduction toadaptive sampling. An ideal reference for statisticians conductingresearch in survey designs and spatial statistics as well asresearchers working in the environmental, ecological, publichealth, and biomedical sciences.

Adaptive Sampling:
* Provides a comprehensive, fully integrated introduction toadaptive sampling theory and practice
* Describes recent research findings
* Introduces readers to a wide range of adaptive samplingstrategies and techniques
* Includes numerous real-world examples from environmentalpollution studies, surveys of rare animal and plant species,studies of contagious diseases, marketing surveys, mineral andfossil-fuel assessments, and more

Über diesen Titel

Über die Autorin bzw. den Autor

STEVEN K. THOMPSON, PhD, is a professor in the Department ofStatistics at Pennsylvania State University.

GEORGE A. F. SEBER, PhD, is a professor in the Department ofStatistics at the University of Auckland, New Zealand.

Von der hinteren Coverseite

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

Details zur Ausgabe

• Verlag: John Wiley & Sons
• Erscheinungsdatum: 1996
• Sprache: Englisch
• ISBN 10: 0471558710
• ISBN 13: 9780471558712
• Einband: Tapa dura
• Anzahl der Seiten: 286
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: Nicht verfügbar