Parameter estimation from a model grid application to the Gaia RVS spectra

Statistical Methodology

Volumn 9, Issue 1-2, 2012, Pages 55-62

  Bijaoui, A ^a   Recio Blanco, A ^a   de Laverny, P ^a   Ordenovic, C ^a  

^a UNIVERSITÉ CÔTE D'AZUR   (France)

Author keywords

Astrophysical data analysis; Astrophysical data mining; Classification; Decision trees; Model grid; Parameter estimation

Indexed keywords

EID: 81255135935     PISSN: 15723127     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.stamet.2011.07.004     Document Type: Article

References (21)

1. Allende Prieto C. An automated system to classify stellar spectra I. Mon. Not. R. Astron. Soc. 2003, 339:1111-1116.
2. Allende Prieto C. Stellar atmospheric parameters: the four-step program and Gaia's radial velocity spectrometer, classification and discovery in large astronomical surveys. AIP Conf. Proc. 2008, 1082:47-53.
3. Bailer-Jones C.A.L. The ILIUM forward modelling algorithm for multivariate parameter estimation and its application to derive stellar parameters from Gaia spectrophotometry. Mon. Not. R. Astron. Soc. 2010, 403:96-116.
4. Bentley J.L., Friedman J.H. Fast algorithms for constructing minimal spanning trees in coordinate spaces. IEEE Trans. Comput. 1978, 27:97-105.
5. Bijaoui A., Recio-Blanco A., de Laverny P. Parameter estimation from an optimal projections in a local environment, classification and discovery in large astronomical surveys. AIP Conf. Proc. 2008, 1082:54-60.
6. Björck A. Numerical Methods for Least Squares Problems 1996, SIAM, Philadelphia, p. 260.
7. Epanechnikov V.A. Theory Probab. Appl. 1969, 14:153-158.
8. Gonzalez O.R., Küper C., Jung K., Naval P.C., Mendoza E. Parameter estimation using simulated annealing for S-system models of biochemical networks. Bioinformatics 2007, 23:480-486.
9. Gustafsson B., Edvardsson B., Erikson K., Jørgensen U.G., Norlund Å., Plez B. A grid of MARCS model atmospheres for late-type stars-I. Methods and general properties. Astron. Astrophys. 2008, 486:951-970.
10. Hastie T., Tibshirani R., Friedman J. The Elements of Statistical Learning: Data Mining, Inference, and Prediction 2001, Springer, Francfort, p. 35.
11. Heavens A., Jimenez R., Lahav O. Massive lossless data compression and multiple parameter estimation from Galaxy spectra. Mon. Not. R. Astron. Soc. 2000, 317:965.
12. Heitmann K., Higdon D., Nakhleh C., Habib Salman Cosmic calibration. Astrophys. J. 2006, 646:L1-L4.
13. Lee A.B., Wasserman L. Spectral connectivity analysis. J. Amer. Statist. Assoc. 2009, 105:1241-1255.
14. Nelder J.A., Mead R. A simplex method for function minimization. Comput. J. 1965, 7:308-313.
15. Nichol R.C., Chong S., Connolly A.J., Davies S., Genovese C., Hopkins A.M., Miller C.J., Moore A.W., Pelleg D., Richards G.T., Schneider J., Szapudi I., Wasserman L. Computational astrostatistics: fast and efficient tools for analysing huge astronomical data sources. Statistical Challenges in Astronomy. Third Statistical Challenges in Modern Astronomy 2003, 265-278. Springer, New York. E.D. Feigelson, G. Babu (Eds.).
16. P. Ram, D. Lee, H. Ouyang, A.G. Gray, Rank-approximate nearest neighbor search: retaining meaning and speed in high dimensions, in: Adv. in Neural Inf. Proc. Syst., NIPS, vol. 22, 2010.
17. Recio-Blanco A., Bijaoui A., de Laverny P. Automated derivation of stellar atmospheric parameters and chemical abundances: the MATISSE algorithm. Mon. Not. R. Astron. Soc. 2006, 370:141-150.
18. Richards J.W., Freeman P.E., Lee A.B., Schafer C.M. Accurate parameter estimation for star formation history in galaxies using SDSS spectra. Mon. Not. R. Astron. Soc. 2009, 399:1044-1057.
19. Tegmark M., Taylor A.N., Heavens A.F. Karhunen-Loeve eigenvalue problems in cosmology: how to tackle large data sets?. Astrophys. J. 1997, 480:22-35.
20. White R. Astronomical applications of oblique decision trees, classification and parametrization of unresolved galaxies with Gaia, classification and discovery in large astronomical surveys. AIP Conf. Proc. 2008, 1082:37-43.
21. Wilkinson M.I., et al. Spectroscopic survey of the Galaxy with Gaia-II. The expected science yield from the royal velocity spectrometer. Mon. Not. R. Astron. Soc. 2005, 359:1306-1335.