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Riemann Estimation for Replicated Environmental Sampling Designs | Science Publications

机译:复制环境采样设计的Riemann估计|英特尔®开发人员专区科学出版物

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> In many environmental surveys the population under study is made up of biological units scattered over a planar region. A variable is considered on each unit and the target parameter generally turns out to be the population total of the variable. In order to estimate the population total, field scientists commonly replicate a suitable design on the study region. Replicated environmental designs basically rely on the selection of a set of sample points, in such a way that each sample point corresponds to a single design replicate. Frequently, the sample points are located uniformly and independently over the planar region, even if more effective strategies are actually available. The population total is subsequently estimated by using the mean of the estimates obtained in each design replicate. However, this pooled estimator may be improved by considering a suitable weighted mean - rather than the simple mean - of the estimates. Thus, we propose a Riemann estimator of the population total which is actually borrowed from the Monte Carlo integration setting. The suggested estimator displays appealing performance from both theoretical and practical perspectives.
机译: >在许多环境调查中,所研究的人口由散布在平坦区域的生物单位组成。每个单元上都会考虑一个变量,而目标参数通常是该变量的总数。为了估计总人口,野外科学家通常在研究区域复制合适的设计。复制的环境设计基本上依赖于一组采样点的选择,以使每个采样点对应一个设计复制。通常,即使实际上有更有效的策略,采样点也会在平面区域上均匀且独立地定位。随后,使用每个设计重复项中获得的估计值的平均值来估计总体。但是,可以通过考虑适当的加权均值-而不是简单的均值-来改进此合并的估计量。因此,我们提出了人口总数的黎曼估计量,该估计数实际上是从蒙特卡洛积分设置中借用的。建议的估算器从理论和实践的角度都显示出有吸引力的性能。

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