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EM algorithms for multivariate Gaussian mixture models with truncated and censored data. (English) Zbl 1255.62308
Summary: We present expectation-maximization (EM) algorithms for fitting multivariate Gaussian mixture models to data that are truncated, censored or truncated and censored. These two types of incomplete measurements are naturally handled together through their relation to the multivariate truncated Gaussian distribution. We illustrate our algorithms on synthetic and flow cytometry data.

62N01 Censored data models
62H99 Multivariate analysis
65C60 Computational problems in statistics (MSC2010)
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