Analytic methods for cosmological likelihoods

Monthly Notices of the Royal Astronomical Society

Volumn 408, Issue 2, 2010, Pages 865-875

  Taylor, A N ^a   Kitching, T D ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

Cosmology: theory; Large scale structure of Universe; Methods: analytical; Methods: data analysis; Methods: statistical

Indexed keywords

BAYESIAN NETWORKS; MARKOV PROCESSES; MONTE CARLO METHODS; NEWTON-RAPHSON METHOD;

ANALYTIC METHOD; COSMOLOGY: THEORY; LARGE SCALE STRUCTURE OF UNIVERSE; LIKELIHOOD ANALYSIS; MARGINALIZATION; METHODS. DATA ANALYSIS; METHODS:ANALYTICAL; METHODS:STATISTICAL; NEWTON'S METHODS; NUISANCE PARAMETER;

COSMOLOGY;

EID: 78649428848     PISSN: 00358711     EISSN: 13652966     Source Type: Journal    
DOI: 10.1111/j.1365-2966.2010.17201.x     Document Type: Article

References (38)

1. Bassett B. A., Corasaniti P. S., Kunz M., 2004, ApJ, 617, L1
2. Beltran M., Garcia-Bellido J., Lesgourgues J., Liddle A. R., Slosar A., 2005, Phys. Rev. D, 71, 063532
3. Bretthorst G., 1988, Lecture Notes Ser. Vol. 48, Bayesian Spectrum Analysis and Parameter Estimation. Springer-Verlag, New York
4. Bridle S. L., Crittenden R., Melchiorri A., Hobson M. P., Kneissl R., Lasenby A. N., 2002, MNRAS, 335, 1193
5. Eisenstein D., Hu W., 1997, ApJ, 511, 5
6. Gamerman D., 1997, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference. Chapman and Hall, New York
7. Gull S. F., 1989, in Skilling J., ed., Maximum Entropy and Bayesian Methods. Kluwer, Dordrecht, p. 511
8. Heavens A. F., Taylor A. N., 1995, MNRAS, 275, 483
9. Heavens A. F., Kitching T. D., Taylor A. N., 2006, MNRAS, 373, 105
10. Heavens A. F., Kitching T. D., Verde L., 2007, MNRAS, 380, 1029
11. Jeffreys H., 1961, Theory of Probability, 3rd edn., Oxford Univ. Press, Oxford
12. Kaiser N., 1988, MNRAS, 231, 149
13. Kass R. E., Raftery A. E., 1995, J. Am. Statistical Association, 90, 773
14. Kitching T., Amara A., 2009, 398, 2134
15. Kosowsky A., Milosavljevic M., Jimenez R., 2002, Phys. Rev. D, 66, 063007
16. Lepage G. P., 1978, J. Comput. Phys., 27, 192
17. Lewis A., Bridle S., 2002, Phys. Rev. D, 66, 103511
18. Liddle A. R., 2009, Annu. Rev. Nuclear Part. Sci., 59, 95
19. MacKay D. J. C., 2003, Information theory, inference and learning algorithms. Cambridge Univ. Press, Cambridge
20. Mukherjee P., Parkinson D., Corasaniti P. S., Liddle A. R., Kunz M., 2006, MNRAS, 369, 1725
21. Press W. H., Flannery B. P., Teukolsky S. A., Vetterling W. T., 1989, Numerical Recipes: The Art of Scientific Computing. Cambridge Univ. Press, Cambridge
22. Refregier A., Amara A., Kitching T. D., Rassat A., Scaramella A., Weller J., 2010, preprint (arXiv:1001.0061)
23. Schwartz G., 1987, Ann. Statist., 5, 461
24. Serra P., Heavens A., Melchiorri A., 2007, MNRAS, 379, 169
25. Skilling J., 2004, in Fischer R., Von Toussaint U., Preuss R., eds, AIP Conf. Proc. Vol. 735, Baysian Inference and Maximum Entropy Methods in Science and Engineering. Am. Inst. Phys., New York, p. 395
26. Slosar A. et al., 2003, MNRAS, 341, L29
27. Smith R. et al., 2003, MNRAS, 341, 1311
28. Spergel D. et al., 2003, ApJS, 148, 175
29. Taylor A. N., Watts P., 2001, MNRAS, 328, 1027
30. Taylor A. N., Kitching T., Bacon D., Heavens A., 2007, MNRAS. 374, 1377
31. Tegmark M., 1997, Phys. Rev. D, 55, 5895
32. Tegmark M., Taylor A. N., Heavens A. F., 1997, ApJ, 480, 22
33. Tegmark M. et al., 2004, Phys. Rev. D, 69, 103501
34. Trotta R., 2007, MNRAS, 378, 72
35. Trotta R., 2008, Contemporary Phys., 49, 71
36. Verde L. et al., 2003, ApJS, 148, 195
37. Woodbury M. A., 1950, Inverting modified matrices, Memorandum Rept. 42, 4. Statistical Research Group, Princeton Univ. Press, Princeton, NJ
38. Zhang F., 2005, The Schur Complement and its Applications. Springer, New York