A discrete probabilistic model for analyzing pairwise comparison matrices

Sumito Kurata and Etsuo Hamada

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 15, 3801-3815

Abstract: The pairwise comparison matrix is often used for the estimation of the priorities in the analytic hierarchy process. In this paper, we propose an estimation method based on the discrete probabilistic expression of each choice. Moreover, we show numerical examples to compare our method with commonly used ones. As a result, it is shown that, using a robust divergence measure for the estimation, the proposed method can extract the priorities more stably even if some outlying observations are included.

Date: 2019
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DOI: 10.1080/03610926.2018.1481975

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