gmm_diag and gmm_full: C++ classes for multi-threaded Gaussian mixture models and Expectation-Maximisation
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Curtin, Ryan
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Abstract
Statistical modelling of multivariate data through a convex mixture of Gaussians, also known as a Gaussian mixture model (GMM), has many applications in fields such as signal processing, econometrics, and pattern recognition (Bishop 2006). Each component (Gaus-sian) in a GMM is parameterised with a weight, mean vector (centroid), and covariance matrix.
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The Journal of Open Source Software
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2
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18
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© 2017 Authors of JOSS papers retain copyright and release the work under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Applied Statistics
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Sanderson, C; Curtin, R, gmm_diag and gmm_full: C++ classes for multi-threaded Gaussian mixture models and Expectation-Maximisation, The Journal of Open Source Software, 2017, 2 (18)