Vertex finding by sparse model-based clustering

Frühwirth, Rudolf and Eckstein, Korbinian and Frühwirth-Schnatter, Sylvia (2016) Vertex finding by sparse model-based clustering. Journal of Physics: Conference Series, 762 (1). pp. 1-5. ISSN 1742-6596

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Abstract

The application of sparse model-based clustering to the problem of primary vertex finding is discussed. The observed z-positions of the charged primary tracks in a bunch crossing are modeled by a Gaussian mixture. The mixture parameters are estimated via Markov Chain Monte Carlo (MCMC). Sparsity is achieved by an appropriate prior on the mixture weights. The results are shown and compared to clustering by the expectation-maximization (EM) algorithm.

Item Type: Article
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Version of the Document: Published
Depositing User: Gertraud Novotny
Date Deposited: 23 Mar 2018 11:19
Last Modified: 07 May 2018 17:29
Related URLs:
FIDES Link: https://bach.wu.ac.at/d/research/results/84753/
URI: https://epub.wu.ac.at/id/eprint/6173

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