Adaptive cluster path sampling

Abstract

          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.

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