SCHIMEK, Michael G., Alena MYSICKOVA and Eva BUDINSKÁ. An Inference and Integration Approach for the Consolidation of Ranked Lists. COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION. PHILADELPHIA: TAYLOR & FRANCIS INC, 2012, vol. 41, No 7, p. 1152-1166. ISSN 0361-0918. doi:10.1080/03610918.2012.625843.
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Basic information
Original name An Inference and Integration Approach for the Consolidation of Ranked Lists
Authors SCHIMEK, Michael G. (40 Austria, guarantor), Alena MYSICKOVA (276 Germany) and Eva BUDINSKÁ (703 Slovakia, belonging to the institution).
Edition COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, PHILADELPHIA, TAYLOR & FRANCIS INC, 2012, 0361-0918.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10103 Statistics and probability
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 0.295
RIV identification code RIV/00216224:14110/12:00060591
Organization unit Faculty of Medicine
Doi http://dx.doi.org/10.1080/03610918.2012.625843
UT WoS 000304853800017
Keywords in English Cross-entropy Monte Carlo; Kendall's tau; Moderate deviation; Partial list; Random degeneration; Rank aggregation; Spearman's footrule; Top-k ranked list
Tags International impact
Changed by Changed by: Mgr. Michal Petr, učo 65024. Changed: 15. 8. 2012 09:39.
Abstract
In this article, we describe a new approach that combines the estimation of the lengths of highly conforming sublists with their stochastic aggregation, to deal with two or more rankings of the same set of objects. The goal is to obtain a much smaller set of informative common objects in a new rank order. The input lists can be of large or huge size, their rankings irregular and incomplete due to random and missing assignments. A moderate deviation-based inference procedure and a cross-entropy Monte Carlo technique are used to handle the combinatorial complexity of the task. Two alternative distance measures are considered that can accommodate truncated list information. Finally, the outlined approach is applied to simulated data that was motivated by microarray meta-analysis, an important field of application.
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