The Past, Present, and Future of Multidimensional Scaling
The Past, Present, and Future of Multidimensional Scaling
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多维尺度的过去、现在和未来
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
I. Borg
中科院分区：
文献类型：
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作者：
P. Groenen;I. Borg
多维尺度(MDS)已成为统计学家和应用研究人员的标准工具。它的成功归功于它对潜在复杂的结构数据的简单和容易解释的表示。这些数据通常嵌入到二维地图中，其中感兴趣的对象(项目、属性、刺激、受访者等)对应于这样的点，即彼此接近的点在经验上相似，而相距较远的点则不同。在本文中，我们向几位重要的MDS开发人员致敬，并对MDS开发中的里程碑进行了主观概述。我们还讨论了MDS的现状，并对其未来进行了简要的展望。
Multidimensional scaling (MDS) has established itself as a standard tool for statisticians and applied researchers. Its success is due to its simple and easily interpretable representation of potentially complex structural data. These data are typically embedded into a 2-dimensional map, where the objects of interest (items, attributes, stimuli, respondents, etc.) correspond to points such that those that are near to each other are empirically similar, and those that are far apart are different. In this paper, we pay tribute to several important developers of MDS and give a subjective overview of milestones in MDS developments. We also discuss the present situation of MDS and give a brief outlook on its future.