JSM 2004 - Toronto

Abstract #301638

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Activity Number: 221
Type: Contributed
Date/Time: Tuesday, August 10, 2004 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract - #301638
Title: Clustering Error Rate in Temporal Data
Author(s): Nicoleta Serban*+ and Larry Wasserman
Companies: Carnegie Mellon University and Carnegie Mellon University
Address: 5000 Forbes Ave., Baker Hall 232, Pittsburgh, PA, 15217,
Keywords: clustering ; clustering error rate ; temporal gene expression data ; temporal data
Abstract:

We propose a technique for estimation of the clustering error rate when clustering a large number of nonconstant curves.We estimate the error due to the fact that we are clustering the estimated rather than the true curves. We obtain an asymptotic confidence bound for the clustering estimation error based on estimated confidence sets of the nonconstant curves. The method we use for uniform confidence set estimation was introduced by Beran and Dumbgen (1998). The clustering error rate can be used to infer how much information is lost when a small number of time points is used and when the signal-to-noise ratio is low. Our motivating example is temporal gene expression data but the method is very general.

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