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Geodesic Monte Carlo on Embedded Manifolds

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  • Simon Byrne
  • Mark Girolami

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  • Simon Byrne & Mark Girolami, 2013. "Geodesic Monte Carlo on Embedded Manifolds," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(4), pages 825-845, December.
    • Handle: RePEc:bla:scjsta:v:40:y:2013:i:4:p:825-845
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    File URL: http://hdl.handle.net/10.1111/sjos.12036
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    References listed on IDEAS

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    1. Beskos, A. & Pinski, F.J. & Sanz-Serna, J.M. & Stuart, A.M., 2011. "Hybrid Monte Carlo on Hilbert spaces," Stochastic Processes and their Applications, Elsevier, vol. 121(10), pages 2201-2230, October.
    2. Hankin, Robin K. S., 2010. "A Generalization of the Dirichlet Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i11).
    3. Harshinder Singh, 2002. "Probabilistic model for two dependent circular variables," Biometrika, Biometrika Trust, vol. 89(3), pages 719-723, August.
    4. Mark Girolami & Ben Calderhead, 2011. "Riemann manifold Langevin and Hamiltonian Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(2), pages 123-214, March.
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    Cited by:

    1. Daniel Simpson, 2014. "Contribution to the Discussion of the Paper “Geodesic Monte Carlo on Embedded Manifolds”," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 16-18, March.
    2. Takaaki Koike & Marius Hofert, 2019. "Markov Chain Monte Carlo Methods for Estimating Systemic Risk Allocations," Papers 1909.11794, arXiv.org, revised May 2020.
    3. Jia Liu & John M. Maheu & Yong Song, 2024. "Identification and forecasting of bull and bear markets using multivariate returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 723-745, August.
    4. Gallant, A. Ronald, 2023. "Variance–covariance from a metropolis chain on a curved, singular manifold," Journal of Econometrics, Elsevier, vol. 235(2), pages 843-861.
    5. Cyril Bachelard & Apostolos Chalkis & Vissarion Fisikopoulos & Elias Tsigaridas, 2023. "Randomized geometric tools for anomaly detection in stock markets," Post-Print hal-04223511, HAL.
    6. Cyril Bachelard & Apostolos Chalkis & Vissarion Fisikopoulos & Elias Tsigaridas, 2022. "Randomized geometric tools for anomaly detection in stock markets," Papers 2205.03852, arXiv.org, revised May 2022.
    7. Justyna Wróblewska, 2015. "Common Trends and Common Cycles – Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 7(2), pages 91-110, June.
    8. Kenneth W. Latimer & David J. Freedman, 2023. "Low-dimensional encoding of decisions in parietal cortex reflects long-term training history," Nature Communications, Nature, vol. 14(1), pages 1-24, December.
    9. Arthur Pewsey & Eduardo García-Portugués, 2021. "Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-58, March.
    10. Janice L. Scealy, 2021. "Comments on: Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 68-70, March.
    11. Takaaki Koike & Marius Hofert, 2020. "Markov Chain Monte Carlo Methods for Estimating Systemic Risk Allocations," Risks, MDPI, vol. 8(1), pages 1-33, January.

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