EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 583 (November 2015) A&A, 583 (2015) A94 References
Free Access
Issue
A&A
Volume 583, November 2015
Article Number A94
Number of page(s) 9
Section Stellar atmospheres
DOI https://doi.org/10.1051/0004-6361/201527120
Published online 02 November 2015
  1. Acuna, E., & Rodriguez, C. 2004, Classification, Clustering and Data Mining Applications (Heidelberg: Springer Verlag), 639 [Google Scholar]
  2. Adibekyan, V. Z., Santos, N. C., Sousa, S. G., & Israelian, G. 2011, A&A, 535, L11 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  3. Adibekyan, V. Z., Sousa, S. G., Santos, N. C., et al. 2012, A&A, 545, A32 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  4. Adibekyan, V. Z., Figueira, P., Santos, N. C., et al. 2013, A&A, 554, A44 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  5. Adibekyan, V. Z., González Hernández, J. I., Delgado Mena, E., et al. 2014, A&A, 564, L15 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  6. Adibekyan, V. Z., Benamati, L., Santos, N. C., et al. 2015, MNRAS, 450, 1900 [NASA ADS] [CrossRef] [Google Scholar]
  7. Anders, E., & Grevesse, N. 1989, Geochim. Cosmochim. Acta, 53, 197 [NASA ADS] [CrossRef] [Google Scholar]
  8. Batista, S. F. A., Adibekyan, V. Z., Sousa, S. G., et al. 2014, A&A, 564, A43 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  9. Battistini, C., & Bensby, T. 2015, A&A, 577, A9 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  10. Bertran de Lis, S., Delgado Mena, E., Adibekyan, V. Z., Santos, N. C., & Sousa, S. G. 2015, A&A, 576, A89 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  11. Blanco-Cuaresma, S., Soubiran, C., Heiter, U., et al. 2015, A&A, 577, A47 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  12. Carling, K. 1998, Resistant outlier rules and the non-Gaussian case, Working Paper Series 2001:7, IFAU – Institute for Evaluation of Labour Market and Education Policy [Google Scholar]
  13. De Silva, G. M., Sneden, C., Paulson, D. B., et al. 2006, AJ, 131, 455 [NASA ADS] [CrossRef] [Google Scholar]
  14. De Silva, G. M., Freeman, K. C., Asplund, M., et al. 2007, AJ, 133, 1161 [NASA ADS] [CrossRef] [Google Scholar]
  15. De Silva, G. M., Freeman, K. C., & Bland-Hawthorn, J. 2009, PASA, 26, 11 [NASA ADS] [CrossRef] [Google Scholar]
  16. De Silva, G. M., D’Orazi, V., Melo, C., et al. 2013, MNRAS, 431, 1005 [NASA ADS] [CrossRef] [Google Scholar]
  17. Freeman, K., & Bland-Hawthorn, J. 2002, ARA&A, 40, 487 [NASA ADS] [CrossRef] [Google Scholar]
  18. González Hernández, J. I., Israelian, G., Santos, N. C., et al. 2010, ApJ, 720, 1592 [NASA ADS] [CrossRef] [Google Scholar]
  19. González Hernández, J. I., Delgado-Mena, E., Sousa, S. G., et al. 2013, A&A, 552, A6 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  20. Hodge, V., & Austin, J. 2004, in Artificial Intelligence Review, 22, 85 (the Netherlands: Kluwer Academic Publishers) [Google Scholar]
  21. Iglewicz, B., & Hoaglin, D. 1993, How to Detect and Handle Outliers, ASQC basic references in quality control (Milwaukee, WI: ASQC Quality Press) [Google Scholar]
  22. Liu, C., Ruchti, G., Feltzing, S., et al. 2015, A&A, 575, A51 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  23. Maldonado, J., Eiroa, C., Villaver, E., Montesinos, B., & Mora, A. 2015, A&A, 579, A20 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. Meléndez, J., Asplund, M., Gustafsson, B., & Yong, D. 2009, ApJ, 704, L66 [NASA ADS] [CrossRef] [Google Scholar]
  25. Mitschang, A. W., De Silva, G., Sharma, S., & Zucker, D. B. 2013, MNRAS, 428, 2321 [NASA ADS] [CrossRef] [Google Scholar]
  26. Mitschang, A. W., De Silva, G., Zucker, D. B., et al. 2014, MNRAS, 438, 2753 [NASA ADS] [CrossRef] [Google Scholar]
  27. Neves, V., Santos, N. C., Sousa, S. G., Correia, A. C. M., & Israelian, G. 2009, A&A, 497, 563 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  28. Nissen, P. E. 2015, A&A, 579, A52 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  29. Nomoto, K., Kobayashi, C., & Tominaga, N. 2013, ARA&A, 51, 457 [NASA ADS] [CrossRef] [Google Scholar]
  30. Önehag, A., Gustafsson, B., & Korn, A. 2014, A&A, 562, A102 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  31. Quillen, A. C., Anguiano, B., De Silva, G., et al. 2015, MNRAS, 450, 2354 [NASA ADS] [CrossRef] [Google Scholar]
  32. Ramírez, I., Meléndez, J., & Asplund, M. 2009, A&A, 508, L17 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  33. Ramírez, I., Bajkova, A. T., Bobylev, V. V., et al. 2014, ApJ, 787, 154 [NASA ADS] [CrossRef] [Google Scholar]
  34. Rousseeuw, P. J., & Leroy, A. M. 1987, Robust Regression and Outlier Detection (New York: John Wiley & Sons, Inc.) [Google Scholar]
  35. Schuler, S. C., Flateau, D., Cunha, K., et al. 2011, ApJ, 732, 55 [NASA ADS] [CrossRef] [Google Scholar]
  36. Sheskin, D. J. 2007, Handbook of Parametric and Nonparametric Statistical Procedures, 4th edn. (Chapman & Hall/CRC) [Google Scholar]
  37. Shiffler, R. E. 1988, The American Statistician, 42, 79 [Google Scholar]
  38. Sousa, S. G., Santos, N. C., Mayor, M., et al. 2008, A&A, 487, 373 [NASA ADS] [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  39. Spina, L., Randich, S., Palla, F., et al. 2014a, A&A, 568, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  40. Spina, L., Randich, S., Palla, F., et al. 2014b, A&A, 567, A55 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  41. Tabernero, H. M., Montes, D., & González Hernández, J. I. 2012, A&A, 547, A13 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  42. Tabernero, H. M., Montes, D., Gonzalez Hernandez, J. I., & Ammler-von Eiff, M. 2015, A&A, in press [Google Scholar]
  43. Tsantaki, M., Sousa, S. G., Adibekyan, V. Z., et al. 2013, A&A, 555, A150 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  44. Tukey, J. W. 1977, Exploratory Data Analysis (Addison-Wesley) [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.