Configuration and Classification of Clusters in n-Dimensions
GEORGIA UNIV ATHENS DEPT OF STATISTICSAND COMPUTER SCIENCE
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Many experiments involve measuring a number of response variables simultaneously. As a result of giving one stimulus to an experimental unit, what the author obtains is not just one response but several responses. In statistical language, one deals with a multivariate situation as opposed to univariate situations. Usually, many stimuli, called factors, are considered at many levels in the same experiment. Many statistical techniques are available to analyze this type of data and to draw conclusions therefrom. The present work considers one such technique, the identification of subgroups of individuals on the basis of responses, i.e., a special case of cluster analysis. Many different algorithms proposed for detecting clusters have been reviewed. These fall into two classes-- those which detect clusters of variables--factor analysis--and those which detect clusters of experimental units--cluster analysis. What the author has done in the present work lies in between these two techniques.
- Statistics and Probability