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article · Biometrics · 2006

Adaptive Web Sampling

Steven K. Thompson

Cited by 79Abstract and details only

Abstract

A flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values. The new designs have certain advantages compared with previously existing adaptive and link-tracing designs, including control over sample sizes and of the proportion of effort allocated to adaptive selections. Efficient inference involves averaging over sample paths consistent with the minimal sufficient statistic. A Markov chain resampling method makes the inference computationally feasible. The designs are evaluated in network and spatial settings using two empirical populations: a hidden human population at high risk for HIV/AIDS and an unevenly distributed bird population.

Cite this paper

APA 7

Thompson, S. K. (2006). Adaptive Web Sampling. Biometrics, 62(4), 1224–1234. https://doi.org/10.1111/j.1541-0420.2006.00576.x

MLA 9

Thompson, Steven K. “Adaptive Web Sampling.” Biometrics, vol. 62, no. 4, 2006, pp. 1224–34, https://doi.org/10.1111/j.1541-0420.2006.00576.x.

Chicago

Thompson, Steven K. 2006. “Adaptive Web Sampling.” Biometrics 62 (4): 1224–34. https://doi.org/10.1111/j.1541-0420.2006.00576.x.

Harvard

Thompson, S.K. (2006) ‘Adaptive Web Sampling’, Biometrics, 62(4), pp. 1224–1234. Available at: https://doi.org/10.1111/j.1541-0420.2006.00576.x.

BibTeX
@article{thompson2006adaptive,
  title = {{Adaptive Web Sampling}},
  author = {Thompson, Steven K.},
  journal = {Biometrics},
  volume = {62},
  number = {4},
  pages = {1224--1234},
  year = {2006},
  doi = {10.1111/j.1541-0420.2006.00576.x}
}

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