Strip Adaptive Cluster Sampling: Probability Proportional to Size Selection of Primary Units

Biometrics ◽  
1997 ◽  
Vol 53 (3) ◽  
pp. 1092 ◽  
Author(s):  
Jeffrey S. Pontius
Keyword(s):  
Cluster Sampling ◽  
Adaptive Cluster Sampling ◽  
Size Selection ◽  
Sampling Probability ◽  
Selection Of

Adaptive sampling

2019 ◽  
pp. 219-239
Author(s):  
David G. Hankin ◽  
Michael S. Mohr ◽  
Ken B. Newman
Keyword(s):  
Rare Species ◽  
Adaptive Sampling ◽  
Sampling Procedure ◽  
Cluster Sampling ◽  
Single Individual ◽  
Adaptive Cluster Sampling ◽  
Sampling Strategies ◽  
Good Sense ◽  
Total Cost ◽  
Selection Of

The abundance of rare species of plants and animals may often prove difficult to estimate due to the isolated patchy distribution of individuals. Adaptive sampling may prove more effective than other sampling strategies for such species. In adaptive cluster sampling an initial SRS of population units is selected. Further adaptive sampling in the neighborhood of these units is then carried out whenever the value of y in a selected unit meets or exceeds a criterion value, c, which may often be just a single individual. This sampling procedure can be shown to lead to selection of clusters of units for which, with the exception of edge units, all units in the selected clusters have y≥c. If the initial sample is large enough to encounter some isolated patches of individuals, this approach may outperform SRS with mean-per-unit estimation. Drawbacks of this approach include the facts that the eventual number of population units which will need to be measured is random and unknown prior to execution of the survey, and it is difficult to specify the magnitude of the adaptive sampling criterion, c. Therefore, the total cost and time needed to complete an adaptive sampling survey can be highly unpredictable. Nevertheless, the theory is intriguing and has obvious intuitive appeal. Once a very rare individual has been encountered, it makes good sense to search very carefully in the neighborhood of the location where that rare individual has been found.

scholarly journals Predictive framework for codend size selection of brown shrimp (Crangon crangon) in the North Sea beam-trawl fishery

PLoS ONE ◽  
2018 ◽  
Vol 13 (7) ◽  
pp. e0200464 ◽  
Author(s):  
Juan Santos ◽  
Bent Herrmann ◽  
Daniel Stepputtis ◽  
Claudia Günther ◽  
Bente Limmer ◽  
...  
Keyword(s):  
North Sea ◽  
Brown Shrimp ◽  
Beam Trawl ◽  
Crangon Crangon ◽  
Size Selection ◽  
Trawl Fishery ◽  
The North ◽  
Sea Beam ◽  
The North Sea ◽  
Selection Of

Size Selection of Atlantic Rangia Clams, Rangia cuneata, by Blue Crabs, Callinectes sapidus

Estuaries ◽  
1994 ◽  
Vol 17 (3) ◽  
pp. 668 ◽  
Author(s):  
Elizabeth L. Ebersole ◽  
Victor S. Kennedy
Keyword(s):  
Callinectes Sapidus ◽  
Blue Crabs ◽  
Size Selection ◽  
Rangia Cuneata ◽  
Selection Of

Estimation of rare and clustered population variance in adaptive cluster sampling

2018 ◽  
Vol 48 (21) ◽  
pp. 5387-5400
Author(s):  
Muhammad Nouman Qureshi ◽  
Sadia Khalil ◽  
Chang-Tai Chao ◽  
Muhammad Hanif
Keyword(s):  
Cluster Sampling ◽  
Adaptive Cluster Sampling ◽  
Population Variance

Stratified adaptive cluster sampling

Biometrika ◽  
1991 ◽  
Vol 78 (2) ◽  
pp. 389-397 ◽  
Author(s):  
STEVEN K. THOMPSON
Keyword(s):  
Cluster Sampling ◽  
Adaptive Cluster Sampling

An Exon Trapping System Providing Size Selection of Spliced Clones and Facilitating Direct Cloning

1994 ◽  
pp. 169-181
Author(s):  
Nicole A. Datson ◽  
Geoffrey M. Duyk ◽  
Lau A. J. Blonden ◽  
Gert-Jan B. Van Ommen ◽  
Johan T. Den Dunnen
Keyword(s):  
Direct Cloning ◽  
Size Selection ◽  
Exon Trapping ◽  
Selection Of

Inverse Adaptive Cluster Sampling

2021 ◽  
pp. 179-192
Author(s):  
Raosaheb Latpate ◽  
Jayant Kshirsagar ◽  
Vinod Kumar Gupta ◽  
Girish Chandra
Keyword(s):  
Cluster Sampling ◽  
Adaptive Cluster Sampling
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