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A three‐dimensional object point process for detection of cosmic filaments

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  • Radu S. Stoica
  • Vicent J. Martínez
  • Enn Saar

Abstract

Summary. We propose to apply an object point process to delineate filaments of the large scale structure in red shift catalogues automatically. We illustrate the feasibility of the idea on an example of the recent 2dF Galaxy Redshift Survey, describe the procedure and characterize the results.

Suggested Citation

  • Radu S. Stoica & Vicent J. Martínez & Enn Saar, 2007. "A three‐dimensional object point process for detection of cosmic filaments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(4), pages 459-477, August.
    • Handle: RePEc:bla:jorssc:v:56:y:2007:i:4:p:459-477
    DOI: 10.1111/j.1467-9876.2007.00587.x
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    File URL: https://doi.org/10.1111/j.1467-9876.2007.00587.x
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    References listed on IDEAS

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    1. Stoica, R.S. & Gregori, P. & Mateu, J., 2005. "Simulated annealing and object point processes: Tools for analysis of spatial patterns," Stochastic Processes and their Applications, Elsevier, vol. 115(11), pages 1860-1882, November.
    2. van Lieshout, M.N.M. & Stoica, R.S., 2006. "Perfect simulation for marked point processes," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 679-698, November.
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    Cited by:

    1. Bianca Maria Colosimo & Luca Pagani & Marco Grasso, 2024. "Modeling spatial point processes in video-imaging via Ripley’s K-function: an application to spatter analysis in additive manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 429-447, January.
    2. T. Rajala & D. J. Murrell & S. C. Olhede, 2018. "Detecting multivariate interactions in spatial point patterns with Gibbs models and variable selection," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1237-1273, November.
    3. Merrilee Hurn & Peter J. Green & Fahimah Al‐Awadhi, 2008. "A Bayesian hierarchical model for photometric red shifts," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(4), pages 487-504, September.

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