Free Access
Issue
A&A
Volume 619, November 2018
Article Number A172
Number of page(s) 15
Section Stellar structure and evolution
DOI https://doi.org/10.1051/0004-6361/201834058
Published online 22 November 2018
  1. Andrieu, C., & Thoms, J. 2008, Stat. Comput., 18, 343 [CrossRef] [Google Scholar]
  2. Angulo, C., Arnould, M., Rayet, M., et al. 1999, Nucl. Phys. A, 656, 3 [NASA ADS] [CrossRef] [Google Scholar]
  3. Antia, H. M., & Basu, S. 2011, J. Phys. Conf. Ser., 271, 012034 [NASA ADS] [CrossRef] [Google Scholar]
  4. Asplund, M., Grevesse, N., & Sauval, A. J. 2005, in Series Cosmic Abundances as Records of Stellar Evolution and Nucleosynthesis, eds. T. G. Barnes, & F. N. Bash, III, ASP Conf. Ser., 336, 25 [NASA ADS] [Google Scholar]
  5. Aver, E., Olive, K. A., Porter, R. L., & Skillman, E. D. 2013, J. Cosmol. Astropart. Phys., 11, 017 [NASA ADS] [CrossRef] [Google Scholar]
  6. Ball, W. H., Beeck, B., Cameron, R. H., & Gizon, L. 2016, A&A, 592, A159 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  7. Balser, D. S. 2006, AJ, 132, 2326 [NASA ADS] [CrossRef] [Google Scholar]
  8. Basu, S. 2016, Liv. Rev. Sol. Phys., 13, 2 [NASA ADS] [CrossRef] [Google Scholar]
  9. Basu, S., & Antia, H. M. 2008, Phys. Rep., 457, 217 [NASA ADS] [CrossRef] [Google Scholar]
  10. Basu, S., & Christensen-Dalsgaard, J. 1997, A&A, 322, L5 [NASA ADS] [Google Scholar]
  11. Baumann, P., Ramírez, I., Meléndez, J., Asplund, M., & Lind, K. 2010, A&A, 519, A87 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  12. Bazot, M. 2013, in EAS Pub. Ser., eds. G. Alecian, Y. Lebreton, O. Richard, & G. Vauclair, 63, 105 [CrossRef] [Google Scholar]
  13. Bazot, M., Bourguignon, S., & Christensen-Dalsgaard, J. 2008, Mem. Soc. Astron. It., 79, 660 [NASA ADS] [Google Scholar]
  14. Bazot, M., Ireland, M. J., Huber, D., et al. 2011, A&A, 526, L4 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  15. Bazot, M., Campante, T. L., Chaplin, W. J., et al. 2012, A&A, 544, A106 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  16. Bazot, M., Christensen-Dalsgaard, J., Gizon, L., & Benomar, O. 2016, MNRAS, 460, 1254 [NASA ADS] [CrossRef] [Google Scholar]
  17. Bishop, C. M. 1995, Neural Networks for Pattern Recognition (New York, USA: Oxford University Press, Inc.) [Google Scholar]
  18. Böhm-Vitense, E. 1958, Z. Astrophys., 46, 108 [Google Scholar]
  19. Bouvier, A., & Wadhwa, M. 2010, Nat. Geosci, 3, 637 [NASA ADS] [CrossRef] [Google Scholar]
  20. Boyajian, T. S., McAlister, H. A., van Belle, G., et al. 2012, ApJ, 746, 101 [NASA ADS] [CrossRef] [Google Scholar]
  21. Boyajian, T. S., von Braun, K., van Belle, G., et al. 2013, ApJ, 771, 40 [NASA ADS] [CrossRef] [Google Scholar]
  22. Brooks, S. P., & Gelman, A. 1998, J. Comput. Graphical Stat., 7, 434 [Google Scholar]
  23. Carlos, M., Nissen, P. E., & Meléndez, J. 2016, A&A, 587, A100 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. Casagrande, L., Flynn, C., Portinari, L., Girardi, L., & Jimenez, R. 2007, MNRAS, 382, 1516 [NASA ADS] [CrossRef] [Google Scholar]
  25. Casagrande, L., Portinari, L., Glass, I. S., et al. 2014, MNRAS, 439, 2060 [NASA ADS] [CrossRef] [Google Scholar]
  26. Castro, M., Vauclair, S., & Richard, O. 2007, A&A, 463, 755 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  27. Cayrel de Strobel, G., Knowles, N., Hernandez, G., & Bentolila, C. 1981, A&A, 94, 1 [NASA ADS] [Google Scholar]
  28. Christensen-Dalsgaard, J. 1982, MNRAS, 199, 735 [Google Scholar]
  29. Christensen-Dalsgaard, J. 2002, Rev. Mod. Phys., 74, 1073 [NASA ADS] [CrossRef] [Google Scholar]
  30. Christensen-Dalsgaard, J. 2008a, Ap&SS, 316, 13 [NASA ADS] [CrossRef] [Google Scholar]
  31. Christensen-Dalsgaard, J. 2008b, Ap&SS, 316, 113 [NASA ADS] [CrossRef] [Google Scholar]
  32. Clayton, D. 1968, Principles of Stellar Evolution and Nucleosynthesis (Chicago: University of Chicago Press) [Google Scholar]
  33. Creevey, O. L., Monteiro, M. J. P. F. G., Metcalfe, T. S., et al. 2007, ApJ, 659, 616 [NASA ADS] [CrossRef] [Google Scholar]
  34. Creevey, O. L., Doǧan, G., Frasca, A., et al. 2012, A&A, 537, A111 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  35. Datson, J., Flynn, C., & Portinari, L. 2012, MNRAS, 426, 484 [NASA ADS] [CrossRef] [Google Scholar]
  36. Datson, J., Flynn, C., & Portinari, L. 2014, MNRAS, 439, 1028 [NASA ADS] [CrossRef] [Google Scholar]
  37. Deal, M., Escobar, M. E., Vauclair, S., et al. 2017, A&A, 601, A127 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  38. Dos Santos, L. A., Meléndez, J., Do Nascimento, J.-D., et al. 2016, A&A, 592, A156 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  39. Doǧan, G., Metcalfe, T. S., Deheuvels, S., et al. 2013, ApJ, 763, 49 [NASA ADS] [CrossRef] [Google Scholar]
  40. Emilio, M., Kuhn, J. R., Bush, R. I., & Scholl, I. F. 2012, ApJ, 750, 135 [NASA ADS] [CrossRef] [Google Scholar]
  41. Formicola, A., Imbriani, G., Costantini, H., et al. 2004, Phys. Lett. B, 591, 61 [NASA ADS] [CrossRef] [Google Scholar]
  42. Fröhlich, C., & Lean, J. 2004, A&ARv, 12, 273 [NASA ADS] [CrossRef] [Google Scholar]
  43. Frühwirth-Schnatter, S. 2006, Finite Mixture and Markov Switching Models Springer Series in Statistics (New York: Springer) [Google Scholar]
  44. Fukugita, M., & Kawasaki, M. 2006, ApJ, 646, 691 [NASA ADS] [CrossRef] [Google Scholar]
  45. Gabriel, M. 1964, Ann. Astrophys., 27, 141 [NASA ADS] [Google Scholar]
  46. Gabriel, M. 1967, Ann. Astrophys., 30, 745 [NASA ADS] [Google Scholar]
  47. Gelman, A., & Rubin, D. B. 1992, Stat. Sci., 7, 457 [NASA ADS] [CrossRef] [Google Scholar]
  48. Gough, D. 1977, in Problems of Stellar Convection, eds. E. A. Spiegel, J.-P. Zahn (Berlin: Springer Verlag), Lect. Notes Phys., 71, 15 [NASA ADS] [CrossRef] [Google Scholar]
  49. Gough, D. O. 1990, in Astrophysics: Recent Progress and Future Possibilities, eds. B. Gustafsson, & P. E. Nissen, 13 [Google Scholar]
  50. Gough, D. O. 2012, in Progress in Solar/Stellar Physics with Helio-and Asteroseismology, eds. H. Shibahashi, M. Takata, & A. E. Lynas-Gray, ASP Conf. Ser., 462, 429 [NASA ADS] [Google Scholar]
  51. Gregory, P. C. 2005, Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica Support (Cambridge: Cambridge University Press), 455 [CrossRef] [MathSciNet] [Google Scholar]
  52. Grevesse, N., & Sauval, A. J. 1998, Space Sci. Rev., 85, 161 [NASA ADS] [CrossRef] [Google Scholar]
  53. Gustafsson, B. 1998, Space Sci. Rev., 85, 419 [NASA ADS] [CrossRef] [Google Scholar]
  54. Gustafsson, B. 2008, Phys. Scr. Vol. T, 130, 014036 [NASA ADS] [CrossRef] [Google Scholar]
  55. Guzik, J. A., Watson, L. S., & Cox, A. N. 2006, Mem. Soc. Astron. It., 77, 389 [NASA ADS] [Google Scholar]
  56. Hastings, W. K. 1970, Biometrika, 57, 97 [CrossRef] [MathSciNet] [Google Scholar]
  57. Houdek, G., Trampedach, R., Aarslev, M. J., & Christensen-Dalsgaard, J. 2017, MNRAS, 464, L124 [NASA ADS] [CrossRef] [Google Scholar]
  58. Iglesias, C. A., & Rogers, F. J. 1996, ApJ, 464, 943 [NASA ADS] [CrossRef] [Google Scholar]
  59. Israelian, G., Delgado Mena, E., Santos, N. C., et al. 2009, Nature, 462, 189 [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
  60. Izotov, Y. I., & Thuan, T. X. 2004, ApJ, 602, 200 [NASA ADS] [CrossRef] [Google Scholar]
  61. Jørgensen, A. C. S., Weiss, A., Mosumgaard, J. R., Silva Aguirre, V., & Sahlholdt, C. L. 2017, MNRAS, 472, 3264 [NASA ADS] [CrossRef] [Google Scholar]
  62. Kim, Y.-C., Demarque, P., Yi, S. K., & Alexander, D. R. 2002, ApJS, 143, 499 [NASA ADS] [CrossRef] [Google Scholar]
  63. King, J. R., Boesgaard, A. M., & Schuler, S. C. 2005, AJ, 130, 2318 [NASA ADS] [CrossRef] [Google Scholar]
  64. Kjeldsen, H., Bedding, T. R., & Christensen-Dalsgaard, J. 2008, ApJ, 683, L175 [NASA ADS] [CrossRef] [Google Scholar]
  65. Lebreton, Y., & Goupil, M. J. 2014, A&A, 569, A21 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  66. Liang, F., Liu, C., & Carroll, R. 2010, Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples, Wiley Series in Computational Statistics (Chichester: Wiley), 357 [CrossRef] [Google Scholar]
  67. Lorenzo-Oliveira, D., Freitas, F. C., Meléndez, J., et al. 2018, A&A, 619, A73 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  68. Mahdi, D., Soubiran, C., Blanco-Cuaresma, S., & Chemin, L. 2016, A&A, 587, A131 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  69. Meléndez, J. 2014, in Setting the Scene for Gaia andLAMOST, eds. S. Feltzing, G. Zhao, N. A. Walton, & P. Whitelock, IAU Symp., 298, 331 [NASA ADS] [Google Scholar]
  70. Meléndez, J., & Ramírez, I. 2007, ApJ, 669, L89 [NASA ADS] [CrossRef] [Google Scholar]
  71. Meléndez, J., Dodds-Eden, K., & Robles, J. A. 2006, ApJ, 641, L133 [NASA ADS] [CrossRef] [Google Scholar]
  72. Meléndez, J., Schuster, W. J., Silva, J. S., et al. 2010, A&A, 522, A98 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  73. Meléndez, J., Schirbel, L., Monroe, T. R., et al. 2014, A&A, 567, L3 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  74. Metropolis, N. 1953, J. Chem. Phys., 21, 1087 [NASA ADS] [CrossRef] [Google Scholar]
  75. Miglio, A., & Montalbán, J. 2005, A&A, 441, 615 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  76. Mittag, M., Schröder, K. P., Hempelmann, A., González-Pérez, J. N., & Schmitt, J. H. M. M. 2016, A&A, 591, A89 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  77. Monroe, T. R., Meléndez, J., Ramírez, I., et al. 2013, ApJ, 774, L32 [NASA ADS] [CrossRef] [Google Scholar]
  78. Moore, K., & Garaud, P. 2016, ApJ, 817, 54 [NASA ADS] [CrossRef] [Google Scholar]
  79. Nissen, P. E. 2015, A&A, 579, A52 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  80. Nissen, P. E., Silva Aguirre, V., Christensen-Dalsgaard, J., et al. 2017, A&A, 608, A112 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  81. Olive, K., & Group, P. D. 2014, Chin. Phys. C, 38, 090001 [NASA ADS] [CrossRef] [MathSciNet] [Google Scholar]
  82. Olive, K. A., & Skillman, E. D. 2004, ApJ, 617, 29 [NASA ADS] [CrossRef] [Google Scholar]
  83. Pearson, K. 1895, Proc. R. Soc. London Ser., 58, 240 [Google Scholar]
  84. Pickles, A. J. 1998, PASP, 110, 863 [NASA ADS] [CrossRef] [Google Scholar]
  85. Planck Collaboration XIII. 2016, A&A, 594, A13 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  86. Porto de Mello, G. F., & Da Silva, L. 1997, ApJ, 482, L89 [NASA ADS] [CrossRef] [Google Scholar]
  87. Porto de Mello, G. F., Da Silva, R., Da Silva, L., & De Nader, R. V. 2014, A&A, 563, A52 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  88. Ramírez, I., Asplund, M., Baumann, P., Meléndez, J., & Bensby, T. 2010, A&A, 521, A33 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  89. Ramírez, I., Meléndez, J., Bean, J., et al. 2014, A&A, 572, A48 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  90. Reese, D. R., Chaplin, W. J., Davies, G. R., et al. 2016, A&A, 592, A14 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  91. Rodgers, J. L., & Nicewander, W. A. 1988, Am. Stat., 42, 59 [CrossRef] [Google Scholar]
  92. Rodríguez-López, C., MacDonald, J., & Moya, A. 2012, MNRAS, 419, L44 [NASA ADS] [CrossRef] [Google Scholar]
  93. Rogers, F. J., & Nayfonov, A. 2002, ApJ, 576, 1064 [NASA ADS] [CrossRef] [Google Scholar]
  94. Rosenthal, J. S. 2008, in Handbook of Markov Chain Monte Carlo, eds. S. Brooks, A. Gelman, G. Jones, & X. L. Meng (Boca Raton, Florida: Chapman and Hall/CRC Press) [Google Scholar]
  95. Roxburgh, I. W., & Vorontsov, S. V. 1994, MNRAS, 267, 297 [NASA ADS] [Google Scholar]
  96. Roxburgh, I. W., & Vorontsov, S. V. 2003, A&A, 411, 215 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  97. Silva Aguirre, V., Basu, S., Brandão, I. M., et al. 2013, ApJ, 769, 141 [NASA ADS] [CrossRef] [Google Scholar]
  98. Silva Aguirre, V., Lund, M. N., Antia, H. M., et al. 2017, ApJ, 835, 173 [NASA ADS] [CrossRef] [Google Scholar]
  99. Sonoi, T., Samadi, R., Belkacem, K., et al. 2015, A&A, 583, A112 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  100. Spina, L., Meléndez, J., Karakas, A. I., et al. 2016, A&A, 593, A125 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  101. Spina, L., Meléndez, J., Karakas, A. I., et al. 2018, MNRAS, 474, 2580 [NASA ADS] [Google Scholar]
  102. Stello, D., Chaplin, W. J., Bruntt, H., et al. 2009, ApJ, 700, 1589 [NASA ADS] [CrossRef] [Google Scholar]
  103. Takeda, Y., & Tajitsu, A. 2009, PASJ, 61, 471 [NASA ADS] [Google Scholar]
  104. Tarantola, A. 2004, Inverse Problem Theory and Methods for Model Parameter Estimation (Philadelphia, USA: Society for Industrial and Applied Mathematics) [Google Scholar]
  105. Tassoul, M. 1980, ApJS, 43, 469 [NASA ADS] [CrossRef] [Google Scholar]
  106. Thompson, M. J. 1991, in Challenges to Theories of the Structure of Moderate-Mass Stars, eds. D. Gough, & J. Toomre (Berlin: Springer Verlag), Lect. Notes Phys., 388, 61 [NASA ADS] [CrossRef] [Google Scholar]
  107. Trampedach, R., Stein, R. F., Christensen-Dalsgaard, J., Nordlund, Å., & Asplund, M. 2014, MNRAS, 445, 4366 [NASA ADS] [CrossRef] [Google Scholar]
  108. Tucci Maia, M., Ramírez, I., Meléndez, J., et al. 2016, A&A, 590, A32 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  109. van Leeuwen, F. 2007, Astrophys, Space Sci. Lib., 350 [CrossRef] [Google Scholar]
  110. White, T. R., Huber, D., Mann, A. W., et al. 2018, MNRAS, 477, 4403 [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.