The Annals of Applied Statistics
- Ann. Appl. Stat.
- Volume 2, Number 3 (2008), 1056-1077.
Distance-based clustering of sparsely observed stochastic processes, with applications to online auctions
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.
Ann. Appl. Stat., Volume 2, Number 3 (2008), 1056-1077.
First available in Project Euclid: 13 October 2008
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Peng, Jie; Müller, Hans-Georg. Distance-based clustering of sparsely observed stochastic processes, with applications to online auctions. Ann. Appl. Stat. 2 (2008), no. 3, 1056--1077. doi:10.1214/08-AOAS172. https://projecteuclid.org/euclid.aoas/1223908052
- Supplementary material: Supplement A: eBay codes.
- Supplementary material: Supplement B: R functions used for FPCA and conditional distance analysis.