EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 590 (June 2016) A&A, 590 (2016) A80 References
Free Access
Issue
A&A
Volume 590, June 2016
Article Number A80
Number of page(s) 16
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/201527013
Published online 16 May 2016
  1. Aird, J., Nandra, K., Laird, E. S., et al. 2010, MNRAS, 401, 2531 [NASA ADS] [CrossRef] [Google Scholar]
  2. Aird, J., Coil, A. L., Georgakakis, A., et al. 2015, MNRAS, 451, 1892 [NASA ADS] [CrossRef] [Google Scholar]
  3. Akaike, H. 1973, in 2nd International Symposium on Information Theory, Academiai Kiado, reprinted in Selected Papers of Hirotugu Akaike (Springer 1998), 199 [Google Scholar]
  4. Akylas, A., Georgakakis, A., Georgantopoulos, I., Brightman, M., & Nandra, K. 2012, A&A, 546, A98 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  5. Alexander, D. M., & Hickox, R. C. 2012, New A Rev., 56, 93 [NASA ADS] [CrossRef] [Google Scholar]
  6. Andreon, S. 2012, in Astrostatistical Challenges for the New Astronomy, ed. J. Hilbe (Springer), 41 [Google Scholar]
  7. Andreon, S., & Hurn, M. 2013, Statistical Analysis and Data Mining, 6, 15 [Google Scholar]
  8. Arnouts, S., Cristiani, S., Moscardini, L., et al. 1999, MNRAS, 310, 540 [NASA ADS] [CrossRef] [Google Scholar]
  9. Ballantyne, D. R., Everett, J. E., & Murray, N. 2006, ApJ, 639, 740 [NASA ADS] [CrossRef] [Google Scholar]
  10. Barger, A. J., Cowie, L. L., Mushotzky, R. F., et al. 2005, AJ, 129, 578 [NASA ADS] [CrossRef] [Google Scholar]
  11. Boyle, B. J., Griffiths, R. E., Shanks, T., Stewart, G. C., & Georgantopoulos, I. 1993, MNRAS, 260, 49 [NASA ADS] [CrossRef] [Google Scholar]
  12. Boyle, B. J., Shanks, T., Georgantopoulos, I., Stewart, G. C., & Griffiths, R. E. 1994, MNRAS, 271, 639 [NASA ADS] [CrossRef] [Google Scholar]
  13. Braccesi, A., Zitelli, V., Bonoli, F., & Formiggini, L. 1980, A&A, 85, 80 [NASA ADS] [Google Scholar]
  14. Brightman, M., & Ueda, Y. 2012, MNRAS, 423, 702 [NASA ADS] [CrossRef] [Google Scholar]
  15. Buchner, J., Georgakakis, A., Nandra, K., et al. 2015, ApJ, 802, 89 [NASA ADS] [CrossRef] [Google Scholar]
  16. Burlon, D., Ajello, M., Greiner, J., et al. 2011, ApJ, 728, 58 [NASA ADS] [CrossRef] [Google Scholar]
  17. Cappelluti, N., Brusa, M., Hasinger, G., et al. 2009, A&A, 497, 635 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  18. Chiappetti, L., Clerc, N., Pacaud, F., et al. 2013, MNRAS, 429, 1652 [NASA ADS] [CrossRef] [Google Scholar]
  19. Comastri, A., Setti, G., Zamorani, G., & Hasinger, G. 1995, A&A, 296, 1 [NASA ADS] [Google Scholar]
  20. Cowie, L. L., Songaila, A., Hu, E. M., & Cohen, J. G. 1996, AJ, 112, 839 [Google Scholar]
  21. Daddi, E., Alexander, D. M., Dickinson, M., et al. 2007, ApJ, 670, 173 [NASA ADS] [CrossRef] [Google Scholar]
  22. Ebrero, J., Carrera, F. J., Page, M. J., et al. 2009, A&A, 493, 55 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  23. Feroz, F., & Hobson, M. P. 2008, MNRAS, 384, 449 [NASA ADS] [CrossRef] [Google Scholar]
  24. Feroz, F., Hobson, M. P., & Bridges, M. 2009, MNRAS, 398, 1601 [NASA ADS] [CrossRef] [Google Scholar]
  25. Feroz, F., Hobson, M. P., Cameron, E., & Pettitt, A. N. 2013, ArXiv e-prints [arXiv:1306.2144] [Google Scholar]
  26. Ferrarese, L., & Merritt, D. 2000, ApJ, 539, L9 [NASA ADS] [CrossRef] [Google Scholar]
  27. Fiore, F., Puccetti, S., Grazian, A., et al. 2012, A&A, 537, A16 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  28. Fontanot, F., De Lucia, G., Monaco, P., Somerville, R. S., & Santini, P. 2009, MNRAS, 397, 1776 [NASA ADS] [CrossRef] [Google Scholar]
  29. Fotopoulou, S., Georgantopoulos, I., Hasinger, G., et al. 2016, A&A, 587, A142 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  30. Gebhardt, K., Bender, R., Bower, G., et al. 2000, ApJ, 539, L13 [NASA ADS] [CrossRef] [Google Scholar]
  31. Gehrels, N. 1986, ApJ, 303, 336 [NASA ADS] [CrossRef] [Google Scholar]
  32. Gelman, A., Carlin, J., Stern, H., et al. 2013, Bayesian Data Analysis, Third Edition, Chapman & Hall/CRC Texts in Statistical Science (Taylor & Francis) [Google Scholar]
  33. Gelman, A., Hwang, J., & Vehtari, A. 2014, Statistics and Computing, 24, 997 [Google Scholar]
  34. Gilli, R., Comastri, A., & Hasinger, G. 2007, A&A, 463, 79 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  35. Gregory, P. 2005, Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with ‘Mathematica’ Support (Cambridge University Press) [Google Scholar]
  36. Gültekin, K., Richstone, D. O., Gebhardt, K., et al. 2009, ApJ, 698, 198 [NASA ADS] [CrossRef] [Google Scholar]
  37. Häring, N., & Rix, H.-W. 2004, ApJ, 604, L89 [NASA ADS] [CrossRef] [Google Scholar]
  38. Hasinger, G. 2008, A&A, 490, 905 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  39. Hasinger, G., Miyaji, T., & Schmidt, M. 2005, A&A, 441, 417 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  40. Hiroi, K., Ueda, Y., Akiyama, M., & Watson, M. G. 2012, ApJ, 758, 49 [NASA ADS] [CrossRef] [Google Scholar]
  41. Hopkins, P. F., Hernquist, L., Cox, T. J., et al. 2006, ApJS, 163, 1 [Google Scholar]
  42. Hopkins, P. F., Hernquist, L., Cox, T. J., Robertson, B., & Krause, E. 2007, ApJ, 669, 67 [NASA ADS] [CrossRef] [Google Scholar]
  43. Hsu, L.-T., Salvato, M., Nandra, K., et al. 2014, ApJ, 796, 60 [NASA ADS] [CrossRef] [Google Scholar]
  44. Ilbert, O., Arnouts, S., McCracken, H. J., et al. 2006, A&A, 457, 841 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  45. Iwasawa, K., Gilli, R., Vignali, C., et al. 2012, A&A, 546, A84 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  46. Jones, L. R., McHardy, I. M., Merrifield, M. R., et al. 1997, MNRAS, 285, 547 [Google Scholar]
  47. Kodama, T., Yamada, T., Akiyama, M., et al. 2004, MNRAS, 350, 1005 [NASA ADS] [CrossRef] [Google Scholar]
  48. Kormendy, J., & Bender, R. 2009, ApJ, 691, L142 [NASA ADS] [CrossRef] [Google Scholar]
  49. La Franca, F., & Cristiani, S. 1997, AJ, 113, 1517 [NASA ADS] [CrossRef] [Google Scholar]
  50. La Franca, F., Fiore, F., Comastri, A., et al. 2005, ApJ, 635, 864 [NASA ADS] [CrossRef] [Google Scholar]
  51. Loredo, T. J. 2004, in AIP Conf. Ser. 735, eds. R. Fischer, R. Preuss, & U. V. Toussaint, 195 [Google Scholar]
  52. Maccacaro, T., Gioia, I. M., Avni, Y., et al. 1983, ApJ, 266, L73 [NASA ADS] [CrossRef] [Google Scholar]
  53. Maccacaro, T., Gioia, I. M., & Stocke, J. T. 1984, ApJ, 283, 486 [NASA ADS] [CrossRef] [Google Scholar]
  54. Maccacaro, T., della Ceca, R., Gioia, I. M., et al. 1991, ApJ, 374, 117 [NASA ADS] [CrossRef] [Google Scholar]
  55. Magorrian, J., Tremaine, S., Richstone, D., et al. 1998, AJ, 115, 2285 [NASA ADS] [CrossRef] [Google Scholar]
  56. Malizia, A., Stephen, J. B., Bassani, L., et al. 2009, MNRAS, 399, 944 [NASA ADS] [CrossRef] [Google Scholar]
  57. Marconi, A., & Hunt, L. K. 2003, ApJ, 589, L21 [NASA ADS] [CrossRef] [Google Scholar]
  58. Marconi, A., Risaliti, G., Gilli, R., et al. 2004, MNRAS, 351, 169 [NASA ADS] [CrossRef] [Google Scholar]
  59. Marshall, H. L., Tananbaum, H., Avni, Y., & Zamorani, G. 1983, ApJ, 269, 35 [NASA ADS] [CrossRef] [Google Scholar]
  60. Mathez, G. 1978, A&A, 68, 17 [NASA ADS] [Google Scholar]
  61. Melnyk, O., Plionis, M., Elyiv, A., et al. 2013, A&A, 557, A81 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  62. Miyaji, T., Hasinger, G., & Schmidt, M. 2001, A&A, 369, 49 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  63. Miyaji, T., Hasinger, G., Salvato, M., et al. 2015, ApJ, 804, 104 [NASA ADS] [CrossRef] [Google Scholar]
  64. Page, M. J., & Carrera, F. J. 2000, MNRAS, 311, 433 [NASA ADS] [CrossRef] [Google Scholar]
  65. Page, M. J., Carrera, F. J., Hasinger, G., et al. 1996, MNRAS, 281, 579 [NASA ADS] [CrossRef] [Google Scholar]
  66. Ranalli, P., Comastri, A., Vignali, C., et al. 2013, A&A, 555, A42 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  67. Ranalli, P., Georgantopoulos, I., Corral, A., et al. 2015, A&A, 577, A121 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  68. Salvato, M., Hasinger, G., Ilbert, O., et al. 2009, ApJ, 690, 1250 [CrossRef] [Google Scholar]
  69. Salvato, M., Ilbert, O., Hasinger, G., et al. 2011, ApJ, 742, 61 [NASA ADS] [CrossRef] [Google Scholar]
  70. Santini, P., Fontana, A., Grazian, A., et al. 2009, A&A, 504, 751 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  71. Schmidt, M. 1968, ApJ, 151, 393 [NASA ADS] [CrossRef] [Google Scholar]
  72. Schmidt, M., & Green, R. F. 1983, ApJ, 269, 352 [NASA ADS] [CrossRef] [Google Scholar]
  73. Setti, G., & Woltjer, L. 1989, A&A, 224, L21 [NASA ADS] [Google Scholar]
  74. Silverman, J. D., Green, P. J., Barkhouse, W. A., et al. 2008, ApJ, 679, 118 [NASA ADS] [CrossRef] [Google Scholar]
  75. Skilling, J. 2004, in Bayesian inference and maximum entropy methods in sci- ence and engineering, AIP Conf. Proc., 735, 395 [Google Scholar]
  76. Skilling, J. 2006, Bayesian Analysis, 1, 833 [Google Scholar]
  77. Treister, E., & Urry, C. M. 2006, ApJ, 652, L79 [NASA ADS] [CrossRef] [Google Scholar]
  78. Treister, E., Urry, C. M., & Virani, S. 2009, ApJ, 696, 110 [NASA ADS] [CrossRef] [Google Scholar]
  79. Trotta, R. 2008, Contemporary Physics, 49, 71 [NASA ADS] [CrossRef] [Google Scholar]
  80. Ueda, Y., Akiyama, M., Ohta, K., & Miyaji, T. 2003, ApJ, 598, 886 [NASA ADS] [CrossRef] [Google Scholar]
  81. Ueda, Y., Watson, M. G., Stewart, I. M., et al. 2008, ApJS, 179, 124 [NASA ADS] [CrossRef] [Google Scholar]
  82. Ueda, Y., Akiyama, M., Hasinger, G., Miyaji, T., & Watson, M. G. 2014, ApJ, 786, 104 [NASA ADS] [CrossRef] [Google Scholar]
  83. Vito, F., Gilli, R., Vignali, C., et al. 2014, MNRAS, 445, 3557 [NASA ADS] [CrossRef] [Google Scholar]
  84. Watanabe, S. 2010, J. Machine Learning Res., 11, 3571 [Google Scholar]
  85. Yencho, B., Barger, A. J., Trouille, L., & Winter, L. M. 2009, ApJ, 698, 380 [NASA ADS] [CrossRef] [Google Scholar]
  86. Zubovas, K., & King, A. R. 2012, MNRAS, 426, 2751 [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.