Mean Shift Cluster Recognition Method Implementation in the Nested Sampling Algorithm

Mean Shift Cluster Recognition Method Implementation in the Nested Sampling Algorithm

Nested sampling is an efficient algorithm for the calculation of the Bayesian evidence and posterior parameter probability distributions. It is based on the step-by-step exploration of the parameter space by Monte Carlo sampling with a series of values sets called live points that evolve towards the...

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Bibliographic Details
Main Authors: Martino Trassinelli, Pierre Ciccodicola
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Entropy
Subjects:
nested sampling
cluster analysis
mean shift method
bayesian evidence
model comparison
Online Access:https://www.mdpi.com/1099-4300/22/2/185

Internet

https://www.mdpi.com/1099-4300/22/2/185

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