Open Access
Issue
A&A
Volume 666, October 2022
Article Number A181
Number of page(s) 15
Section Cosmology (including clusters of galaxies)
DOI https://doi.org/10.1051/0004-6361/202243632
Published online 24 October 2022
  1. Abbott, T. M. C., Aguena, M., Alarcon, A., et al. 2022, Phys. Rev. D, 105, 023520 [CrossRef] [Google Scholar]
  2. Aghamousa, A., Aguilar, J., Ahlen, S., et al. 2016, ArXiv e-prints [arXiv:1611.00036] [Google Scholar]
  3. Alarcon, A., Gaztanaga, E., Eriksen, M., et al. 2021, MNRAS, 501, 6103 [NASA ADS] [CrossRef] [Google Scholar]
  4. Alonso, D. 2012, ArXiv e-prints [arXiv:1210.1833] [Google Scholar]
  5. Amendola, L., Appleby, S., Avgoustidis, A., et al. 2018, Liv. Rev. Relativ., 21, 2 [NASA ADS] [CrossRef] [Google Scholar]
  6. Anderson, E., Bai, Z., Bschof, C., et al. 1999, LAPACK Users Guide, 3rd edn. (Philadelphia: SIAM) [CrossRef] [Google Scholar]
  7. Baddeley, A., & Turner, R. 2005, J. Stat. Softw., 12, 1 [CrossRef] [Google Scholar]
  8. Baddeley, A. J., Moyeed, R. A., Howard, C. V., & Boyde, A. 1993, Appl. Stat., 42, 641 [CrossRef] [Google Scholar]
  9. Baddeley, A. J., Møller, J., & Waagepetersen, R. 2000, Stat. Neerl., 54, 329 [CrossRef] [Google Scholar]
  10. Bautista, J. E., Paviot, R., Vargas Magaña, M., et al. 2021, MNRAS, 500, 736 [Google Scholar]
  11. Breton, M.-A., & de la Torre, S. 2021, A&A, 646, A40 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  12. Colombi, S., Szapudi, I., & Szalay, A. S. 1998, MNRAS, 296, 253 [NASA ADS] [CrossRef] [Google Scholar]
  13. Dagum, L., & Menon, R. 1998, Comput. Sci. Eng. IEEE, 5, 46 [CrossRef] [Google Scholar]
  14. Daley, D. J., & Vere-Jones, D. 2003, An Introduction to the Theory of Point Processes (Berlin: Springer-Verlag) [Google Scholar]
  15. Dávila-Kurbán, F., Sánchez, A. G., Lares, M., & Ruiz, A. N. 2021, MNRAS, 506, 4667 [CrossRef] [Google Scholar]
  16. Davis, M., & Peebles, P. J. E. 1983, ApJ, 267, 465 [Google Scholar]
  17. Dawson, K. S., Schlegel, D. J., Ahn, C. P., et al. 2013, AJ, 145, 10 [Google Scholar]
  18. Demina, R., Cheong, S., BenZvi, S., & Hindrichs, O. 2018, MNRAS, 480, 49 [Google Scholar]
  19. Donoso, E. 2019, MNRAS, 487, 2824 [NASA ADS] [CrossRef] [Google Scholar]
  20. Eisenstein, D. J., Zehavi, I., Hogg, D. W., et al. 2005, ApJ, 633, 560 [Google Scholar]
  21. Feldman, H. A., Kaiser, N., & Peacock, J. A. 1994, ApJ, 426, 23 [Google Scholar]
  22. Fiksel, T. 1988, Statistics, 19, 67 [CrossRef] [Google Scholar]
  23. Halton, J. 1960, J. Numer. Math., 2, 84 [CrossRef] [Google Scholar]
  24. Hamilton, A. 1993, ApJ, 417, 19 [NASA ADS] [CrossRef] [Google Scholar]
  25. Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357 [NASA ADS] [CrossRef] [Google Scholar]
  26. He, C.-C. 2021, ApJ, 921, 59 [NASA ADS] [CrossRef] [Google Scholar]
  27. Heck, D., Schlömer, T., & Deussen, O. 2013, ACM Trans. Graph., 32, 1 [Google Scholar]
  28. Hewett, P. C. 1982, MNRAS, 201, 867 [Google Scholar]
  29. Hirschmann, M., Dolag, K., Saro, A., et al. 2014, MNRAS, 442, 2304 [Google Scholar]
  30. Ivezić, Ž., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111 [Google Scholar]
  31. Jakob, W., Rhinelander, J., & Moldovan, D. 2017, pybind11 – Seamless Operability between C++11 and Python, https://github.com/pybind/pybind11 [Google Scholar]
  32. Keihänen, E., Kurki-Suonio, H., Lindholm, V., et al. 2019, A&A, 631, A73 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  33. Kerscher, M. 1999, A&A, 343, 333 [NASA ADS] [Google Scholar]
  34. Kerscher, M., Szapudi, I., & Szalay, A. 2000, ApJ, 535, L13 [NASA ADS] [CrossRef] [Google Scholar]
  35. Landy, S. D., & Szalay, A. S. 1993, ApJ, 412, 64 [Google Scholar]
  36. L’Ecuyer, P., & Lemieux, C. 2002, Recent Advances in Randomized Quasi-Monte Carlo Methods (New York: Springer), 419 [Google Scholar]
  37. Moore, A. W., Connolly, A. J., & Genovese, C. 2001, in Mining the Sky, eds. A. J. Banday, S. Zaroubi, & M. Bartelmann, 71 [CrossRef] [Google Scholar]
  38. Neyman, J., & Scott, E. L. 1958, J. R. Stat. Soc., 20, 1 [Google Scholar]
  39. Niederreiter, H. 1992, Random Number Generation and Quasi-Monte Carlo Methods (Philadelphia: SIAM) [CrossRef] [Google Scholar]
  40. Ohser, J. 1983, Math. Operationsforsch. Stat. Ser. Stat., 14, 63 [Google Scholar]
  41. Owen, A. B. 2017, ArXiv e-prints [arXiv:1706.02808] [Google Scholar]
  42. Owen, A. B., & Rudolf, D. 2021, SIAM Rev., 63, 360 [CrossRef] [Google Scholar]
  43. Peebles, P. J. E. 1980, The Large Scale Structure of the Universe (Princeton: Princeton University Press) [Google Scholar]
  44. Peebles, P. J. E., & Hauser, M. G. 1974, ApJS, 28, 19 [NASA ADS] [CrossRef] [Google Scholar]
  45. Ragagnin, A., Dolag, K., Biffi, V., et al. 2017, Astron. Comput., 20, 52 [Google Scholar]
  46. Ripley, B. D. 1976, J. Appl. Prob., 13, 255 [Google Scholar]
  47. Ripley, B. D. 1988, Statistical Inference for Spatial Processes (Cambridge: Cambridge University Press) [CrossRef] [Google Scholar]
  48. Rivolo, A. R. 1986, ApJ, 301, 70 [NASA ADS] [CrossRef] [Google Scholar]
  49. Ross, A. J., Percival, W. J., Sánchez, A. G., et al. 2012, MNRAS, 424, 564 [Google Scholar]
  50. Ross, A. J., Bautista, J., Tojeiro, R., et al. 2020, MNRAS, 498, 2354 [NASA ADS] [CrossRef] [Google Scholar]
  51. Saunders, W., Rowan-Robinson, M., & Lawrence, A. 1992, MNRAS, 258, 134 [NASA ADS] [Google Scholar]
  52. Shaw, T., Møller, J., & Waagepetersen, R. 2021, Aust. N. Z. J. Stat., 63, 93 [CrossRef] [Google Scholar]
  53. Sinha, M., & Garrison, L. H. 2020, MNRAS, 491, 3022 [Google Scholar]
  54. Stoyan, D., & Stoyan, H. 1994, Fractals, Random Shapes and Point Fields: Methods of Geometrical Statistics (Chichester: John Wiley& Sons) [Google Scholar]
  55. Stoyan, D., & Stoyan, H. 2000, Scand. J. Stat., 27, 641 [CrossRef] [Google Scholar]
  56. Stoyan, D., Kendall, W. S., & Mecke, J. 1995, Stochastic Geometry and its Applications, 2nd edn. (Chichester: John Wiley& Sons) [Google Scholar]
  57. Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nat. Meth., 17, 261 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.