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AuthorSalehi, Mohammad
AuthorPanahbehagh, Bardia
AuthorParvardeh, Afshin
AuthorSmith, David R.
AuthorLei, Yuancai
Available date2023-10-02T05:16:13Z
Publication Date2013
Publication NameEnvironmental and Ecological Statistics
ResourceScopus
ISSN13528505
URIhttp://dx.doi.org/10.1007/s10651-012-0235-y
URIhttp://hdl.handle.net/10576/48156
AbstractAdaptive two-stage sequential sampling (ATSSS) design was developed to observe more rare units and gain higher efficiency, in the sense of having a smaller variance estimator, than conventional sampling designs with equal effort for rare and spatially cluster populations. For certain rare populations, incorporating auxiliary variables into a sampling design can further improve the observation of rare units and increase efficiency. In this article, we develop regression-type estimators for ATSSS so that auxiliary variables can be incorporated into the ATSSS design when warranted. Simulation studies on two populations show that the regression-type estimators can significantly increase the efficiency of ATSSS and the detection of more rare units as compared to conventional sampling counterparts. Simulation of sampling of desert shrubs in Inner Mongolia (one of the two populations studied) showed that by incorporating a GIS auxiliary variable into ATSSS with the regression estimators resulted in a gain in efficiency over ATSSS without the auxiliary variable. Further, we found that the use of the GIS auxiliary variable in a conventional two-stage design with a regression estimator did not show a gain in efficiency.
SponsorAcknowledgments We would like to thank two referees and an associate editor for their helpful suggestions on a previous draft of this article. The authors express their appreciation to the Ministry of Science and Technology and National Natural Sciences Foundation of China for fiscal support in the field work of Tamarix ramosissima population (Project Research Grants 31170588 and 2005DIB5JI42).
Languageen
PublisherSpringer
SubjectAdaptive sampling
Freshwater mussels
GIS auxiliary variable
Optimal coefficient
Rare population
Tamarix ramosissima
TitleRegression-type estimators for adaptive two-stage sequential sampling
TypeArticle
Pagination571-590
Issue Number4
Volume Number20
dc.accessType Abstract Only


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