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Incomplete paired comparisons in case of multiple choice and general log-concave probability density functions
A scoring method based on paired comparison allowing multiple choice is investigated. We allow general log-concave probability density functions for the random variables describing the difference of the objects. This case involves Bradley–Terry models and Thurstone models as well. A sufficient condi...
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Published in: | Central European journal of operations research 2019-06, Vol.27 (2), p.515-532 |
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container_title | Central European journal of operations research |
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creator | Orbán-Mihálykó, Éva Mihálykó, Csaba Koltay, László |
description | A scoring method based on paired comparison allowing multiple choice is investigated. We allow general log-concave probability density functions for the random variables describing the difference of the objects. This case involves Bradley–Terry models and Thurstone models as well. A sufficient condition is proved for the existence and uniqueness of the maximum likelihood estimation of the parameters in case of incomplete comparisons. The axiomatic properties of the method are also investigated. |
doi_str_mv | 10.1007/s10100-018-0568-1 |
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subjects | Analysis Business and Management Decision-making Distribution (Probability theory) Economic models Estimation theory Mathematical models Maximum likelihood estimates (Statistics) Maximum likelihood estimation Methods Operations research Operations Research/Decision Theory Original Paper Parameter estimation Probability density functions Random variables |
title | Incomplete paired comparisons in case of multiple choice and general log-concave probability density functions |
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