Adaptive cluster path sampling

被引:1
|
作者
Lao, Mena [1 ]
Dryver, Arthur [2 ]
机构
[1] Kasetsart Univ, Fac Sci, Dept Stat, 50 Ngam Wong Wan Rd, Bangkok 10900, Thailand
[2] NIDA, Sch Business Adm, Bangkok, Thailand
关键词
Adaptive cluster sampling; adaptive sampling; Horvitz-Thompson estimator; Path sampling; Unequal probability sampling;
D O I
10.1080/03610918.2022.2075388
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Path sampling is one of the economical sampling designs for spatial populations since it provides the capability of sampling all units along a path traveled during a survey. Path sampling is a non-adaptive sampling design; however it is known that the adaptive sampling design provides more precise estimates of the population mean and total than conventional sampling designs. Therefore, the objective of this article is to propose a new sampling design called "adaptive cluster path sampling" using adaptive sampling strategy and conventional path sampling in order to obtain more precise parameter estimate. Two estimators of the population mean and their mean square error were obtained. The efficiency of adaptive cluster path sampling was examined by performing a simulation study, comparing adaptive cluster path sampling to conventional path sampling, adaptive cluster sampling and simple random sampling. According to the simulation results on the blue winged teal data, adaptive cluster path sampling is more efficient than path sampling and adaptive cluster sampling when equal sampling cost is considered.
引用
收藏
页码:2316 / 2329
页数:14
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