Quantifying the efficiency of soil sampling designs: A multivariate approach

被引:0
|
作者
Polona Kalan
Katarina Košmelj
Charles Taillie
Anton Cedilnik
John H. Carson
机构
[1] Slovenian Forestry Institute,Biotechnical Faculty
[2] University of Ljubljana,Center for Statistical Ecology and Environmental Statistics
[3] The Pennsylvania State University,undefined
[4] Shaw Environmental,undefined
来源
Environmental and Ecological Statistics | 2003年 / 10卷
关键词
cost; entropy; information; Kullback–Leibler distance; loss function; random weights; Rohde’s lemma;
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中图分类号
学科分类号
摘要
The objective of this paper is to quantify and compare the loss functions of the standard two-stage design and its composite sample alternative in the context of multivariate soil sampling. The loss function is defined (conceptually) as the ratio of cost over information and measures design inefficiency. The efficiency of the design is the reciprocal of the loss function. The focus of this paper is twofold: (a) we define a measure of multivariate information using the Kullback–Leibler distance, and (b) we derive the variance-covariance structure for two soil sampling designs: a standard two-stage design and its composite sample counterpart. Randomness in the mass of soil samples is taken into account in both designs. A pilot study in Slovenia is used to demonstrate the calculations of the loss function and to compare the efficiency of the two designs. The results show that the composite sample design is more efficient than the two-stage design. The efficiency ratio is 1.3 for pH, 2.0 for C, 2.1 for N, and 2.5 for CEC. The multivariate efficiency ratio is 2.3. These ratios primarily reflect cost ratios; influence of the information is small.
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页码:469 / 482
页数:13
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