Decompositions of information divergences: Recent development, open problems and applications

AIP Conference Proceedings

Volumn 1493, Issue , 2012, Pages 972-976

  Stehlik M ^a  

^a JOHANNES KEPLER UNIVERSITY LINZ   (Austria)

Author keywords

decomposition; deconvolution; information divergence; statistical inference

Indexed keywords

EID: 84873138973     PISSN: 0094243X     EISSN: 15517616     Source Type: Conference Proceeding    
DOI: 10.1063/1.4765604     Document Type: Conference Paper

References (35)

1. M.S. Ali, S.D. Silvey, Journal of Royal Statistical Society, Series B, 28, 131-140 (1966)
2. B. L. Amstadter, Reliability mathematics, McGRAWHILL, 1971, chapter 9
3. R.R. Bahadur, Proc. 5th Berkeley Sympos. on Probab. Theory and Mathem. Statist., 1, eds. L. Le Cam and J. Neyman, 13-26 (1965)
4. R.R. Bahadur, Ann. Mathem. Statist. 38, 303-324 (1967)
5. N. Balakrishnan and M. Stehlík, IFAS res. report Nr. 35. (2008)
6. O.E. Barndorf-Nielsen, Information and Exponential Families In Statistical Theory, John Wiley & Sons, Ltd., New York, 111-115, 1978
7. G.W. Brier, Mon. Wea. Rev., 78, 1-3 (1950)
8. D. W. Coit, and T. Jin, (2000) IIE Transactions 32, 1161-1166 (2000).
9. I. Csiszár, Studia scientiarum Mathematicarum Hungarica, 2, 299-318 (1967)
10. M.H. Degroot, Annals of Mathematical Statistics, 33, 404-419 (1962)
11. Degroot M.H.: Optimal Statistical Decisions, McGraw Hill, New York, 1970.
12. D. Feldman and F. Österreicher, Studia Sci. Math. Hungar., 24, 191-200 (1989)
13. C. Guttenbrunner, Trans. 11th Prague Conf. Inform. Theory, Statist. Dec. Funct., Random Processes, vol. A, 449-456 (1992)
14. L. Györfi, T. Nemetz, Annals of the Inst. Statist. Math, 30, 105-113 (1978)
15. A. Karagrigoriou, K. Mattheou, Comm. Statist. Theory Methods, 39, 472-482 (2010)
16. P.D. Lax, Functional analysis, Wiley-Interscience, 2002
17. F. Liese, I. Vajda, IEEE Transactions on Information Theory, 52, 10, 4394-4412 (2006).
18. A.H. Murphy, J. Appl. Meteor., 12, 595-600 (1973)
19. F. Österreicher, I. Vajda, IEEE Trans. Inform. Theory, 39, 3, 1036-1039 (1993)
20. L. Pardo, Statistical Inference based on divergence measures, Chapman & Hall/CRC, 2006
21. A. Pázman, In: Trans. of 10th Prague Conf. on Information Theory, p. 117-132. Academia Publ. House, Prague, 1988
22. Pázman A, Nonlinear statistical Models., Kluwer Acad. Publ., Dordrecht, 1993, chapters 9.1 and 9.2
23. A. Pázman, Metrika, 44, 9-26 (1996)
24. R.T. Rockafellar, Convex Analysis, Princeton Landmarks in Mathematics and Physics, 1996
25. F. Rublík, Kybernetika 25, 13-25 (1989a)
26. F. Rublík, Kybernetika 25, 117-135 (1989b)
27. V. Sečkárová, In: The 2nd International Workshop od Decision Making with Multiple Imperfect Decision Makers. Held in Conjunction with the 25th Annual Conference on Neural Information Processing Systems (NIPS 2011)
28. M. Stehlík, Metrika 57, 145-164 (2003)
29. M. Stehlík, Statistics & Probability Letters 76, 19-26 (2006).
30. M. Stehlík, Reliability Engineering & System Safety, 93, 1809-1813 (2008).
31. M. Stehlík, International Journal of Reliability, Quality and Safety Engineering, 16(6), 469-481 (2009).
32. M. Stehlík, ESRA Newsletter, (2010), http://www.esrahomepage.org.
33. M. Stehlík, AIP Conference Proceedings, 1281, 1913-1916 (2010)
34. S. Weijs, R. Van Nooijen, N. Van de Giesen, Mon. Weather Rev., 138, 3387-3399 (2010)
35. S. S.Wilks, Mathematical Statistics, JohnWiley & Sons, Inc, New York, 1962.