25. Systematic and Strip Adaptive Cluster Sampling

  1. Steven K. Thompson

Published Online: 10 FEB 2012

DOI: 10.1002/9781118162934.ch25

Sampling, Third Edition

Sampling, Third Edition

How to Cite

Thompson, S. K. (2012) Systematic and Strip Adaptive Cluster Sampling, in Sampling, Third Edition, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118162934.ch25

Author Information

  1. Simon Fraser University, Canada

Publication History

  1. Published Online: 10 FEB 2012
  2. Published Print: 23 FEB 2012

Book Series:

  1. Wiley Series in Probability and Statistics

Book Series Editors:

  1. Walter A. Shewhart and
  2. Samuel S. Wilks

ISBN Information

Print ISBN: 9780470402313

Online ISBN: 9781118162934

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Keywords:

  • estimators;
  • strip adaptive cluster sampling;
  • systematic adaptive cluster sampling

Summary

In this chapter, adaptive cluster sampling designs are considered in which the initial sample is selected in terms of primary units and subsequent additions to the sample are in terms of secondary units. The chapter describes examples of the types of designs in order to estimate the mean number of point objects-representing the locations of animals in a clumped population-in the study region. The chapter provides estimators which are unbiased with the adaptive cluster sampling designs. Since these estimators are, in fact, design-unbiased, the unbiasedness does not depend on any assumptions about the population itself. Estimators such as the Hansen–Hurwitz estimator, the multiplicity estimator of network sampling, and related estimators used in line-intercept sampling achieve unbiasedness by dividing each observation by its selection probability and multiplying by the number of times the unit was selected.

Controlled Vocabulary Terms

cluster sampling; estimator