A Bayesian method for the analysis of deterministic and stochastic time series

Astronomy and Astrophysics

Volumn 546, Issue , 2012, Pages

  Bailer Jones, C A L ^a  

^a MAX PLANCK INSTITUT FÜR ASTRONOMIE   (Germany)

Author keywords

Brown dwarfs; Methods: statistical

Indexed keywords

BAYESIAN METHODS; BROWN DWARFS; CROSS VALIDATION; DETERMINISTIC COMPONENT; ERROR BARS; ERROR MODEL; GAUSSIANS; LIGHT CURVES; MEASUREMENT UNCERTAINTY; METHODS:STATISTICAL; MODEL PARAMETERS; MONTE CARLO SAMPLING; NULL HYPOTHESIS; ORNSTEIN-UHLENBECK PROCESS; SIGNAL VARIABLES; SINUSOIDAL MODEL; STOCHASTIC COMPONENT; STOCHASTIC TIME SERIES; TEMPORAL SAMPLING; TIME SERIES MODELS; TIME VARIABLE; ULTRA COOL DWARFS; UNIVARIATE TIME SERIES;

BAYESIAN NETWORKS; MONTE CARLO METHODS; PROBABILITY DISTRIBUTIONS; RANDOM PROCESSES; STARS; STOCHASTIC SYSTEMS; TIME SERIES; UNCERTAINTY ANALYSIS;

STOCHASTIC MODELS;

EID: 84867363751     PISSN: 00046361     EISSN: 14320746     Source Type: Journal    
DOI: 10.1051/0004-6361/201220109     Document Type: Article

References (26)

1. Bailer-Jones, C. A. L. 2004, A&A, 419, 703
2. Bailer-Jones, C. A. L. 2008, MNRAS, 384, 1145
3. Bailer-Jones, C. A. L. 2009, Int. J. Astrobiol., 8, 213
4. Bailer-Jones, C. A. L. 2011, MNRAS, 416, 1163;
5. Bailer-Jones, C. A. L., & Mundt, R. 2001, A&A, 367, 218 (BJM)
6. Berger, J. O., & Sellke, T. 1987, J. Am. Stat. Associat., 82, 112
7. Berliner, L. M. 1996, in Fundamental Theories of Physics, 79, Maximum Entropy & Bayesian Methods: Proceedings of the 15th International Workshop, eds. K. Hanson, & R. N. Silver, Santa Fe, NM, 1995
8. Brockwell, P. J.,& Davis, R. A. 2002, Introduction to time series and forecasting, 2nd edn. (Springer)
9. Chatfield, C. 1996, The analysis of time series, 5th edn. (London: Chapman & Hall)
10. Christensen, R. 2005, Amer. Statist., 59, 121
11. Gillespie, D. T. 1996a, Phys. Rev. E, 54, 2084
12. Gillespie, D. T. 1996b, Am. J. Phys., 64, 225
13. Jaynes, E. T. 2003, Probability theory. The logic of science (Cambridge University Press)
14. Jones, R. H. 1986, J. Appl. Probab., 23, 89
15. Kadane, J. B., & Lazar, N. A. 2004, J. Am. Stat. Assoc., 99, 465
16. Kass, R., & Raftery, A. 1995, J. Am. Stat. Assoc., 90, 773
17. Kelly, B. C., et al. 2009, ApJ, 698, 895
18. Kozlowski, S., et al. 2010, ApJ, 708, 927
19. MacKay, D. J. C. 2003, Information Theory, Inference and Learning Algorithms (Cambridge University Press)
20. Morales-Calderón, M., Stauffer, J. R., Kirkpatrick, J. D., et al. 2006, ApJ, 653, 1454
21. Radigan, J., Jayawardhana, R., Lafrenière, D., et al. 2012, ApJ, 750, 105
22. Reiners, A., & Basri, G. 2008, ApJ, 684, 1390
23. Spiegelhalter, D. J., Best, N. G., Carlin, B. P., & van der Linde, A. 2002, J. R. Statist. Soc. B, 64, 583
24. Uhlenbeck, G. E., & Ornstein, L. S. 1930, Phys. Rev., 36, 823
25. Vehtari, A., & Lampinen, J. 2002, Neural Comput., 14, 2439
26. von Toussaint, U. 2011, Rev. Mod. Phys., 83, 943