On decompositional algorithms for uniform sampling from \(n\)-spheres and \(n\)-balls. (English) Zbl 1205.65029
The authors describe a universal conditional distribution method for uniform sampling from \(n\)-spheres and \(n\)-balls. The method brings a unifying view on several known algorithms and a possibility to construct some novel variants. The authors give the performance comparison of the known and new algorithms: new algorithms have advantages for dimensions 5, 6, and 7. Dimension 7 is not a limit for new algorithms, but their advantages decline with increasing dimension.
Reviewer: Serghey G. Suvorov (Donetsk)
MSC:
| 65C60 | Computational problems in statistics (MSC2010) |
| 65C05 | Monte Carlo methods |
| 62D05 | Sampling theory, sample surveys |
| 62E15 | Exact distribution theory in statistics |
Keywords:
\(n\)-ball; \(n\)-sphere; uniform distribution; beta distribution; normal distribution; Monte Carlo; simulation; uniform sampling; algorithmsReferences:
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