Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/85097
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Type: Journal article
Title: Highest density difference region estimation with application to flow cytometric data
Author: Duong, T.
Koch, I.
Wand, M.
Citation: Biometrical Journal, 2009; 51(3):504-521
Publisher: Wiley
Issue Date: 2009
ISSN: 0323-3847
1521-4036
Statement of
Responsibility: 
Tarn Duong, Inge Koch, and M. P. Wand
Abstract: Motivated by the needs of scientists using flow cytometry, we study the problem of estimating the region where two multivariate samples differ in density. We call this problem highest density difference region estimation and recognise it as a two-sample analogue of highest density region or excess set estimation. Flow cytometry samples are typically in the order of 10 000 and 100 000 and with dimension ranging from about 3 to 20. The industry standard for the problem being studied is called Frequency Difference Gating, due to Roederer and Hardy (2001). After couching the problem in a formal statistical framework we devise an alternative estimator that draws upon recent statistical developments such as patient rule induction methods. Improved performance is illustrated in simulations. While motivated by flow cytometry, the methodology is suitable for general multivariate random samples where density difference regions are of interest.
Keywords: Flow cytometry; Frequency difference gating; Highest density region; Multivariate density estimation; Patient rule induction method
Rights: Copyright © 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
RMID: 0030007409
DOI: 10.1002/bimj.200800201
Appears in Collections:IPAS publications
Mathematical Sciences publications

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