MULTIVARIATE-ANALYSIS OF SENSORY DATA - A COMPARISON OF METHODS
MULTIVARIATE-ANALYSIS OF SENSORY DATA - A COMPARISON OF METHODS
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DOI：
10.1093/chemse/11.1.19
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发表时间：
1986-01-01
期刊：
影响因子：
3.5
通讯作者：
SMITH, DV
中科院分区：
文献类型：
--
作者：
BIEBER, SL;SMITH, DV
多元统计分析旨在简化复杂数据阵列中存在的关系。在化学意义上，多元方法已被用来解决一些问题，包括神经元的分类和刺激关系的描述。本文提出了层次聚类分析，因子分析和非度量多维尺度的概念性讨论，强调这些程序是如何运作的，每个是如何解释的，以及它们如何相互关联。这些技术被应用到一个单一的化学传感器数据集内的刺激关系。结果被用来提供这些多变量程序的概念性理解，并说明它们之间的相似性和差异。
Multivariate statistical analyses are designed to simplify the relationships that exist within a complex array of data. Within the chemical senses, multivariate methods have been used to address a number of problems, including the classification of neurons and the description of stimulus relationships. This paper presents a conceptual discussion of hierarachical cluster analysis, factor analysis, and non-metric multidimensional scaling, emphasizing how each of these procedures operates, how each is interpreted, and how they relate to one another. These techniques are applied to the stimulus relationships within a single set of chemosensory data. The results are used to provide a conceptual understanding of these multivariate procedures and to illustrate the similarities and differences among them.