von Dr. Rodrigo Herrera
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[1.] Rh/Fragment 150 11 - Diskussion Zuletzt bearbeitet: 2012-07-30 23:32:08 Hindemith | Chen et al. 2006, Fragment, Gesichtet, Rh, SMWFragment, Schutzlevel sysop, Verschleierung |
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Untersuchte Arbeit: Seite: 150, Zeilen: 10-18 |
Quelle: Chen et al. 2006 Seite(n): 8 (preprint), Zeilen: 26-36 |
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5.5.5. Prediction. The calculation of the predictive probability of new data will be averaged over a number of MCMC samples, which are selected from those samples where the algorithm tends to stabilize. Stabilization will be assessed heuristically based on the value of the log-likelihood. Additionally to eliminate the auto-correlation, one sample will be selected from each consecutive set of 10 iterations. For a particular MCMC sample, the predictive probability is attained from two components: the represented and the unrepresented mixtures. In a similar manner to that adopted in the sampling stage, the probability from unrepresented mixtures will be approximated by a finite mixture of Gaussians, whose parameters (μl, Ωl) are drawn from the prior. | 2.4 Prediction
The calculation of the predictive probability of new data will be averaged over a number of MCMC samples, which are selected from those where the algorithm tends to stabilize. Stabilization will be assessed heuristically based on the value of the log-likelihood. Additionally to eliminate the auto-correlation, one sample will be selected from each consecutive set of 10 iterations. For a particular MCMC sample, the predictive probability is attained from two components: the represented and the unrepresented mixtures. In a similar manner to that adopted in the sampling stage, the probability from unrepresented mixtures will be approximated by a finite mixture of Gaussians, whose parameters, (μj, τj) are drawn from the prior. |
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