EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 654 (October 2021) A&A, 654 (2021) A26 References
Open Access
Issue
A&A
Volume 654, October 2021
Article Number A26
Number of page(s) 17
Section Extragalactic astronomy
DOI https://doi.org/10.1051/0004-6361/202039461
Published online 06 October 2021
  1. Aartsen, M. G., Ackermann, M., Adams, J., et al. 2017, ApJ, 843, 112 [NASA ADS] [CrossRef] [Google Scholar]
  2. Aigrain, S., Parviainen, H., & Pope, B. 2016, MNRAS, 459, 2408 [NASA ADS] [Google Scholar]
  3. Ambikasaran, S., Foreman-Mackey, D., Greengard, L., Hogg, D. W., & O’Neil, M. 2015, IEEE Trans. Pattern Anal. Mach. Intell., 38, 252 [NASA ADS] [CrossRef] [Google Scholar]
  4. Andrae, R., Schulze-Hartung, T., & Melchior, P. 2010, ArXiv e-prints [arXiv:1012.3754] [Google Scholar]
  5. Aptekar, R. L., Frederiks, D. D., Golenetskii, S. V., et al. 1995, Space Sci. Rev., 71, 265 [NASA ADS] [CrossRef] [Google Scholar]
  6. Astropy Collaboration (Price-Whelan, A. M., et al.) 2018, AJ, 156, 123 [Google Scholar]
  7. Becker, W., Kramer, M., & Sesana, A. 2018, Space Sci. Rev., 214, 30 [CrossRef] [Google Scholar]
  8. Berlato, F., Greiner, J., & Burgess, J. M. 2019, ApJ, 873, 60 [NASA ADS] [CrossRef] [Google Scholar]
  9. Betancourt, M. 2017, ArXiv e-prints [arXiv:1701.02434] [Google Scholar]
  10. Betancourt, M., & Girolami, M. 2013, ArXiv e-prints [arXiv:1312.0906] [Google Scholar]
  11. Bochner, S. 1934, Ann. Math., 35, 111 [CrossRef] [Google Scholar]
  12. Burgess, J. M., Yu, H.-F., Greiner, J., & Mortlock, D. J. 2017, MNRAS, 476, 1427 [Google Scholar]
  13. Carpenter, B., Gelman, A., Hoffman, M. D., et al. 2017, J. Stat. Softw., 76, 1 [NASA ADS] [CrossRef] [Google Scholar]
  14. Castillo, I. 2012, Sankhya A, 74, 194 [CrossRef] [Google Scholar]
  15. Cline, T. L., Desai, U. D., Teegarden, B. J., et al. 1982, ApJ, 255, L45 [NASA ADS] [CrossRef] [Google Scholar]
  16. Connaughton, V., Briggs, M. S., Goldstein, A., et al. 2015, ApJS, 216, 32 [Google Scholar]
  17. Fernique, P., Allen, M. G., Boch, T., et al. 2015, A&A, 578, A114 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  18. Gabry, J., Simpson, D., Vehtari, A., Betancourt, M., & Gelman, A. 2019, J. R. Stat. Soc. Ser. A, 182, 389 [CrossRef] [Google Scholar]
  19. Genovese, C. R., Miller, C. J., Nichol, R. C., Arjunwadkar, M., & Wasserman, L. 2004, Stat. Sci., 19, 308 [Google Scholar]
  20. Gorski, K. M., Hivon, E., Banday, A. J., et al. 2005, ApJ, 622, 759 [Google Scholar]
  21. Grossman, S. A., & Nowak, M. A. 1994, ApJ, 435, 548 [NASA ADS] [CrossRef] [Google Scholar]
  22. Hadji, A., & Szábo, B. 2019, ArXiv e-prints [arXiv:1904.01383] [Google Scholar]
  23. Harris, C. R., Millman, K. J., Walt, S. J. V. D., et al. 2020, Nature, 585, 357 [CrossRef] [PubMed] [Google Scholar]
  24. Hilbe, J. M., De Souza, R. S., & Ishida, E. E. 2017, Bayesian Models for Astrophysical Data: Using R, JAGS, Python, and Stan (Cambridge University Press) [CrossRef] [Google Scholar]
  25. Hjort, N. L., Holmes, C., Müller, P., & Walker, S. G. 2010, Bayesian Nonparametrics (Cambridge University Press), 28 [CrossRef] [Google Scholar]
  26. Huggins, J. H., & Miller, J. W. 2019, ArXiv e-prints [arXiv:1912.07104] [Google Scholar]
  27. Hunter, J. D. 2007, Comput. Sci. Eng., 9, 90 [NASA ADS] [CrossRef] [Google Scholar]
  28. Hurley, K., Kouveliotou, C., Harmon, A., et al. 1998, Adv. Space Res., 22, 1125 [NASA ADS] [CrossRef] [Google Scholar]
  29. Hurley, K., Briggs, M. S., Kippen, R. M., et al. 1999, ApJS, 120, 399 [NASA ADS] [CrossRef] [Google Scholar]
  30. Hurley, K., Kouveliotou, C., Cline, T., et al. 2000, ApJ, 537, 953 [NASA ADS] [CrossRef] [Google Scholar]
  31. Hurley, K., Pal’shin, V. D., Aptekar, R. L., et al. 2013, ApJS, 207, 39 [Google Scholar]
  32. Hurley, K., Svinkin, D. S., Aptekar, R. L., et al. 2016, ApJ, 829, L12 [NASA ADS] [CrossRef] [Google Scholar]
  33. Hurley, K., Tsvetkova, A. E., Svinkin, D. S., et al. 2019, ApJ, 871, 121 [NASA ADS] [CrossRef] [Google Scholar]
  34. Kozlova, A. V., Israel, G. L., Svinkin, D. S., et al. 2016, MNRAS, 460, 2008 [NASA ADS] [CrossRef] [Google Scholar]
  35. Kumar, R., Carroll, C., Hartikainen, A., & Martin, O. A. 2019, J. Open Source Softw., 4, 1143 [Google Scholar]
  36. Lam, S. K., Pitrou, A., & Seibert, S. 2015, https://doi.org/10.1145/2833157.2833162 [Google Scholar]
  37. Li, T. P., & Ma, Y. Q. 1983, ApJ, 272, 317 [NASA ADS] [CrossRef] [Google Scholar]
  38. Lindgren, F., Lindström, J., & Rue, H. 2010, An Explicit Link Between Gaussian Fields and Gaussian Markov Random Fields: The SPDE Approach (Citeseer) [Google Scholar]
  39. Lyddon, S., Holmes, C., & Walker, S. 2019, Biometrika, 106, 465 [Google Scholar]
  40. Meegan, C., Lichti, G., Bhat, P. N., et al. 2009, ApJ, 702, 791 [NASA ADS] [CrossRef] [Google Scholar]
  41. Milton, P., Coupland, H., Giorgi, E., & Bhatt, S. 2019, Epidemics, 29, 100362 [Google Scholar]
  42. Norris, J. P., Nemiroff, R. J., Bonnell, J. T., et al. 1996, ApJ, 459, 393 [NASA ADS] [CrossRef] [Google Scholar]
  43. Pal’shin, V. D., Hurley, K., Svinkin, D. S., et al. 2013, ApJS, 207, 38 [Google Scholar]
  44. Rahimi, A., & Recht, B. 2008, in Neural Information Processing Systems, eds. J. C. Platt, D. Koller, Y. Singer, & S. T. Roweis (Curran Associates, Inc.), 1177 [Google Scholar]
  45. Remes, S., Heinonen, M., & Kaski, S. 2017, in Advances in Neural Information Processing Systems, 4642 [Google Scholar]
  46. Rubinstein, R. Y., & Kroese, D. P. 2016, Simulation and the Monte Carlo Method, 3rd edn. (Wiley Publishing) [Google Scholar]
  47. Singer, L. P., & Price, L. R. 2016, Phys. Rev. D, 93, 024013 [NASA ADS] [CrossRef] [Google Scholar]
  48. Sinha, S. 2002, JApA, 23, 129 [NASA ADS] [Google Scholar]
  49. Spokoiny, V., & Zhilova, M. 2015, Ann. Stat., 43, 2653 [Google Scholar]
  50. Strong, I. B., Klebesadel, R. W., & Olson, R. A. 1974, ApJ, 188, L1 [NASA ADS] [CrossRef] [Google Scholar]
  51. Suyu, S. H., Bonvin, V., Courbin, F., et al. 2017, MNRAS, 468, 2590 [Google Scholar]
  52. Tak, H., Mandel, K., Van Dyk, D. A., et al. 2017, Ann. Appl. Stat., 11, 1309 [Google Scholar]
  53. Ton, J.-F., Flaxman, S., Sejdinovic, D., & Bhatt, S. 2018, Spatial Stat., 28, 59 [Google Scholar]
  54. Vedrenne, G., Roques, J. P., Schönfelder, V., et al. 2003, A&A, 411, L63 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  55. Vianello, G. 2018, ApJS, 236, 17 [NASA ADS] [CrossRef] [Google Scholar]
  56. Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nat. Methods, 17, 261 [Google Scholar]
  57. Wilkins, D. R. 2019, MNRAS, 489, 1957 [NASA ADS] [CrossRef] [Google Scholar]
  58. Wilks, S. S. 1938, Ann. Math. Stat., 9, 60 [Google Scholar]
  59. Williams, C. K., & Rasmussen, C. E. 1996, in Advances in Neural Information Processing Systems, 514 [Google Scholar]
  60. Yaglom, A. M. 1987, Basic Results, 1, 526 [Google Scholar]
  61. Zoghbi, A., Fabian, A., Reynolds, C., & Cackett, E. 2012, MNRAS, 422, 129 [NASA ADS] [CrossRef] [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.