2022-11-28T05:09:29Zhttps://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/379372021-06-23T10:07:15Zcom_10324_1146com_10324_931com_10324_894col_10324_1262
00925njm 22002777a 4500
dc
Llamazares Rodríguez, Bonifacio
author
2019
The Winsorized mean is a well-known robust estimator of the population mean. It can also be seen as a symmetric aggregation function (in fact, it is an ordered weighted averaging operator), which means that the information sources (for instance, criteria or experts’ opinions) have the same importance. However, in many practical applications (for instance, in many multiattribute decision making problems) it is necessary to consider that the information sources have different importance. For this reason, in this paper we propose a natural generalization of the Winsorized means so that the sources of information can be weighted differently. The new functions, which we will call Winsorized weighted means, are a specific case of the Choquet integral and they are analyzed through several indices for which we give closed-form expressions: the orness degree, k-conjunctiveness and k-disjunctiveness indices, veto and favor indices, Shapley values and interaction indices. We also provide a closed-form expression for the Möbius transform and we show how we can aggregate data so that each information source has the desired weighting and outliers have no influence in the aggregated value.
Group Decision and Negotiation, 2019, vol. 28, n. 5, 907-933.
0926-2644
http://uvadoc.uva.es/handle/10324/37937
10.1007/s10726-019-09623-8
907
5
933
Group Decision and Negotiation
28
1572-9907
An analysis of Winsorized weighted means