TY  - JOUR
TI  - Vertex finding by sparse model-based clustering
AB  - 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.
DO  - http://dx.doi.org/10.1088/1742-6596/762/1/012055
SP  - 012055
PY  - 2016-01-01
JO  - Journal of Physics: Conference Series
AU  - Frühwirth, Rudolf 
AU  - Eckstein, Korbinian 
AU  - Frühwirth-Schnatter, Sylvia 
ER -