Divergence between various estimates of quantized information sources

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1. A. Barron L. Györfi, E. van der Meulen, Distribution estimation consistent in total variation and in two types of information divergence, IEEE Trans. Inform. Theory 38 (1992), 1437-1454. (1992) MR1178189
2. T. Berger, Rate Distortion Theory: A Mathematical Basis for Data Compression, Prentice-Hall, Englewood Cliffs, NJ 1971. (1971) MR0408988
3. H. Chernoff, E. L. Lehmann, The use of maximum likelihood estimates in ${\chi }^2$ tests of goodness of fit, Ann. Math. Statist. 25 (1954), 579-586. (1954) Zbl0056.37103MR0065109
4. B. S. Clarke, A. R. Barron, Information-theoretic asymptotics and Bayes methods, IEEE Trans. Inform. Theory 36 (1990), 453-471. (1990) MR1053841
5. T. M. Cover, J. A. Thomas, Elements of Information Theory, New York, Wiley 1991. (1991) Zbl0762.94001MR1122806
6. N. Cressie, T. R. C. Read, Multinomial goodness of fit tests, J. Roy. Statist. Soc. Ser. A 46 (1984), 440-464. (1984) Zbl0571.62017MR0790631
7. I. Csiszár, Information-type measures of difference of probability distributions and their indirect observation, Studia Sci. Math. Hungar. 2 (1967), 299-318. (1967) MR0219345
8. I. Csiszár, Generalized cutoff rates and Rényi's information measures, IEEE Trans. Inform. Theory 41 (1995), 26-34. (1995) Zbl0822.94003MR1366742
9. R. C. Dahiya, J. Gurland, Pearson chi-squared test of fit with random intervals, Biometrika 59 (1972), 147-153. (1972) Zbl0232.62017MR0314191
10. A. Gersho, R. M. Gray, Vector Quantization and Signal Compression, Kluwer, Boston 1991. (1991) 
11. L. Györfi I. Vajda, E. van der Meulen, Minimum Hellinger distance point estimates consistent under weak family regularity, Mathem. Methods of Statistics 3 (1994), 25-45. (1994) MR1272629
12. L. Györfi I. Vajda, E. van der Meulen, Parameter estimation by projecting on structural families, In: Proc. 5th Prague Symp. on Asympt. Statistics (P. Mandl and H. Hušková, eds.), Physica Verlag, Wien 1994, pp. 261-272. (1994) MR1311945
13. W. C. M. Kallenberg J. Oosterhoff, B. F. Schriever, The number of classes in chi-squared goodness of fit tests, J. Amer. Statist. Assoc. 80 (1985), 959-968. (1985) MR0819601
14. M. Menéndez D. Morales L. Pardo, I. Vajda, Divergence-based estimation and testing of statistical models of classification, J. Multivariate Anal. 54 (1995), 329-354. (1995) MR1345543
15. F. Liese, I. Vajda, Convex Statistical Distances, Teubner, Leipzig 1987. (1987) Zbl0656.62004MR0926905
16. D. S. Moore, A chi-squared statistics with random cell boundaries, Ann. Math. Statist. 42 (1971), 147-156. (1971) MR0275601
17. D. Morales L. Pardo, I. Vajda, Asymptotic divergence of estimates of discrete distributions, J. Statist. Plann. Inference 49, 1995. (1995) MR1368984
18. F. Österreicher, I. Vajda, Statistical information and discrimination, IEEE Trans. Inform. Theory 39 (1993), 1036-1039. (1993) MR1237725
19. F. H. Ruymgaart, A note on chi-square statistics with random cell boundaries, Ann. Statist. 3 (1975), 965-968. (1975) Zbl0325.62015MR0378183
20. M. Teboulle, I. Vajda, Convergence of best $\phi$-entropy estimates, IEEE Trans. Inform. Theory 39 (1993), 297-301. (1993) Zbl0765.94001MR1211512
21. I. Vajda, From perceptron to Boltzman machine: Information processing by cognitive networks, In: Proc. of the Third European School of System Sciences (I. Figuearas, A. Moncho and R. Torres, eds.), Univ. of Valencia, Valencia 1994, pp. 65-68. (1994) 
22. A. Veselý, I. Vajda, Classification of random signals by neural networks, In: Proc. of 14th Internat. Congress of Cybernetics, University of Namur, Namur 1996, in print. (1996)