Ordering Quantiles through Confidence Statements

Ranking variables according to their relevance to predict an outcome is an important task in biomedicine. For instance, such ranking can be used for selecting a smaller number of genes for then applying other sophisticated experiments only on genes identified as important. A nonparametric method cal...

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Bibliographic Details
Main Authors: Cassio P. de Campos, Carlos A. de B. Pereira, Paola M. V. Rancoita, Adriano Polpo
Format: Article
Language:English
Published: MDPI AG 2016-10-01
Series:Entropy
Subjects:
Online Access:http://www.mdpi.com/1099-4300/18/10/357
Description
Summary:Ranking variables according to their relevance to predict an outcome is an important task in biomedicine. For instance, such ranking can be used for selecting a smaller number of genes for then applying other sophisticated experiments only on genes identified as important. A nonparametric method called Quor is designed to provide a confidence value for the order of arbitrary quantiles of different populations using independent samples. This confidence may provide insights about possible differences among groups and yields a ranking of importance for the variables. Computations are efficient and use exact distributions with no need for asymptotic considerations. Experiments with simulated data and with multiple real -omics data sets are performed, and they show advantages and disadvantages of the method. Quor has no assumptions but independence of samples, thus it might be a better option when assumptions of other methods cannot be asserted. The software is publicly available on CRAN.
ISSN:1099-4300