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Hierarchical Grouping to Optimize an Objective Function

Joe H. Ward · Journal of the American Statistical Association · 1963

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Abstract A procedure for forming hierarchical groups of mutually exclusive subsets, each of which has members that are maximally similar with respect to specified characteristics, is suggested for use in large-scale (n > 100) studies when a precise optimal solution for a specified number of groups is not practical. Given n sets, this procedure permits their reduction to n − 1 mutually exclusive sets by considering the union of all possible n(n − 1)/2 pairs and selecting a union having a maximal value for the functional relation, or objective function, that reflects the criterion chosen by the investigator. By repeating this process until only one group remains, the complete hierarchical structure and a quantitative estimate of the loss associated with each stage in the grouping can be obtained. A general flowchart helpful in computer programming and a numerical example are included.

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APA 7

Ward, J. H. (1963). Hierarchical Grouping to Optimize an Objective Function. https://doi.org/10.1080/01621459.1963.10500845

MLA

Ward, Joe H. "Hierarchical Grouping to Optimize an Objective Function." 1963. https://doi.org/10.1080/01621459.1963.10500845.

Chicago

Ward, Joe H. 1963. "Hierarchical Grouping to Optimize an Objective Function.". https://doi.org/10.1080/01621459.1963.10500845.

Harvard

Ward, J. H. 1963, Hierarchical Grouping to Optimize an Objective Function, Journal of the American Statistical Association, available at: https://doi.org/10.1080/01621459.1963.10500845 [Accessed 5 Aug. 2026].

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Title
Hierarchical Grouping to Optimize an Objective Function
Author / contributors
Joe H. Ward
Publisher
Journal of the American Statistical Association
Publication year
1963
Language
English

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