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September 2008 Distance-based clustering of sparsely observed stochastic processes, with applications to online auctions
Jie Peng, Hans-Georg Müller
Ann. Appl. Stat. 2(3): 1056-1077 (September 2008). DOI: 10.1214/08-AOAS172

Abstract

We propose a distance between two realizations of a random process where for each realization only sparse and irregularly spaced measurements with additional measurement errors are available. Such data occur commonly in longitudinal studies and online trading data. A distance measure then makes it possible to apply distance-based analysis such as classification, clustering and multidimensional scaling for irregularly sampled longitudinal data. Once a suitable distance measure for sparsely sampled longitudinal trajectories has been found, we apply distance-based clustering methods to eBay online auction data. We identify six distinct clusters of bidding patterns. Each of these bidding patterns is found to be associated with a specific chance to obtain the auctioned item at a reasonable price.

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Jie Peng. Hans-Georg Müller. "Distance-based clustering of sparsely observed stochastic processes, with applications to online auctions." Ann. Appl. Stat. 2 (3) 1056 - 1077, September 2008. https://doi.org/10.1214/08-AOAS172

Information

Published: September 2008
First available in Project Euclid: 13 October 2008

zbMATH: 1149.62053
MathSciNet: MR2516804
Digital Object Identifier: 10.1214/08-AOAS172

Keywords: Bidder trajectory , clustering of trajectories , Functional data analysis , metric in function space , multidimensional scaling

Rights: Copyright © 2008 Institute of Mathematical Statistics

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Vol.2 • No. 3 • September 2008
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