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Publications - Igor Vajda


Books and chapters (13)
1. * Igor Vajda, E. van der Meulen: Goodness-of-Fit Criteria Based on Observations Quantized by Hypothetical and Empirical Percentiles. Handbook of Fitting Statistical Distributions with R, 1-56. CRC Press, Boca Raton 2010.   Download
2. * Jana Zvárová, Š. Svačina, Zdeněk Valenta, Petr Berka, David Buchtela, Radim Jiroušek, Marek Malý, Vendula Papíková, Jan Peleška, Jan Rauch, Igor Vajda, Arnošt Veselý, Karel Zvára Jr., Miroslav Zvolský: Systémy pro podporu lékařského rozhodování. Biomedicínská informatika 3. Universita Karlova - nakladatelství Karolinum, Praha 2009.   Download
3. * Jana Zvárová, Arnošt Veselý, Igor Vajda: Data, Information and Knowledge. Chapter I. Data Mining and Medical Knowledge Management: Cases and Applications, 1-36. Information Science Reference, Hershey 2009.
4. * Igor Vajda, F. Liese: f-divergences: Sufficiency, deficiency and testing of hypotheses. Advances in Inequalities from Probability Theory and Statistics, 113-149. Nova Publishers, Toronto 2008.   Download
5. * Igor Vajda, Jiří Grim: Neural networks. Systems Science and Cybernetics, 224-248. Eolss Publishers-UNESCO, Oxford 2008.   Download
6. * Igor Vajda: Self Organization as a Synergism of Conservative and Liberal Behavior. Handbook of Systems Science, 171-180. European Systems Union, Athens 1991.
7. * Martin Janžura, Antonín Otáhal, Igor Vajda: Teorie informace. Masarykův ústav vyšších studií ČVUT, Praha 1991.
8. * Igor Vajda: Rényi Distances of Some Diffusion Processes. Probability Theory and Mathematical Statistics, 529-534. Mokslas, Vilnius 1990.
9. * Igor Vajda, J. Přibyl: Error Statistics in Data Networks. Computer Networking, 145-153. NorthHolland, Amsterdam 1990.
10. * Igor Vajda: Asymptotic Rate of Discrimination of Random Processes. Proceedings of 4th Prague Symposium on Asymptotic Statistics, 101-112. Charles University, Prague 1989.
11. * Igor Vajda: Theory of Statistical Inference and Information. Kluwer Academic Publishers, Dordrecht 1989.
12. * Igor Vajda, F. Liese: Convex statistical distances. Teubner-Texte zur Mathematik 95. Teubner, Leipzig 1987.
13. * Igor Vajda: Teória informácie a štatistického rozhodovania. epsilon . vydavatelství Alfa, Bratislava 1982.

Journal articles (103)
1. * W. Stummer, Igor Vajda: On Bregman Distances and Divergences of Probability Measures. IEEE Transactions on Information Theory 58:3 (2012), 1277-1288. Institute of Electrical and Electronics Engineers.   Download
2. * M. Broniatowski, Igor Vajda: Decomposable pseudodistances and applications in statistical estimation. Journal of Statistical Planning and Inference 142:9 (2012), 2574-2585. Elsevier.   Download
3. * Igor Vajda: On metric divergences of probability measures. Kybernetika 45:6 (2009), 885-900. Ústav teorie informace a automatizace AV ČR, v. v. i..   Download
5. * P. Harremoes, Igor Vajda: On the Bahadur-efficient testing of uniformity by means of entropy. IEEE Transactions on Information Theory 54:1 (2008), 321-331. Institute of Electrical and Electronics Engineers.   Download
6. * T. Hobza, L. Pardo, Igor Vajda: Robust median estimator in logisitc regression. Journal of Statistical Planning and Inference 138:12 (2008), 3822-3840. Elsevier.   Download
7. * V. Kůs, D. Morales, Igor Vajda: Extensions of the parametric families of divergences used in statistical inference. Kybernetika 44:1 (2008), 95-112. Ústav teorie informace a automatizace AV ČR, v. v. i..
8. * Jan Šindelář, Igor Vajda, Miroslav Kárný: Stochastic control optimal in the Kullback sense. Kybernetika 44:1 (2008), 53-60. Ústav teorie informace a automatizace AV ČR, v. v. i..   Download
9. * Igor Vajda, P. Harremoës: On the Bahadur-efficient testing of uniformity by means of entropy. IEEE Transactions on Information Theory 54, 321-331. Institute of Electrical and Electronics Engineers.
10. * Igor Vajda, Jana Zvárová: On generalized entropies, Bayesian decisions and statistical diversity. Kybernetika 43:5 (2007), 675-696. Ústav teorie informace a automatizace AV ČR, v. v. i..
11. * Igor Vajda: Asymptotic comparisons of divergence-based goodness-of-fit statistics. Publications of the Statistical Institute of the University of Paris 51, 49-66.
12. * Igor Vajda, W. Stummer: Optimal statistical decisions about some alternative financial models. Journal of Econometrics 137:2 (2007), 441-471. Elsevier.
13. * Igor Vajda, D. Morales, L. Pardo: On efficient estimation in continuous models based on finitely quantized observations. Communications in Statistics - Theory and Methods 35, 1629-1653. Taylor & Francis.
14. * Igor Vajda, F. Liese, D. Morales: Asymptotically sufficient partitions and quantizations. IEEE Transactions on Information Theory 52:12 (2006), 5599-5606. Institute of Electrical and Electronics Engineers.
15. * F. Liese, Igor Vajda: On divergences and informations in statistics and information theory. IEEE Transactions on Information Theory 52:10 (2006), 4394-4412. Institute of Electrical and Electronics Engineers.
16. * A. Berlinet, Igor Vajda: On asymptotic sufficiency and optimality of quantizations. Journal of Statistical Planning and Inference 136:12 (2006), 4217-4237. Elsevier.
17. * Jana Zvárová, Igor Vajda: On Genetic Information, Diversity and Distance. Methods of Information in Medicine 45:2 (2006), 173-179.
18. * Igor Vajda, Arnošt Veselý, Jana Zvárová: On the amount of information resulting from empirical and theoretical knowledge. Revista Mathématica Complutense 18:2 (2005), 275-283. Springer.
19. * Tomáš Hobza, I. Molina, Igor Vajda: On convergence of Fisher informations in continuous models with quantized observations. Test 14:1 (2005), 151-179.
20. * Igor Vajda, E. C. van der Meulen: On minimum divergence adaptation of discrete bivariate distributions to given marginals. IEEE Transactions on Information Theory 51:1 (2005), 313-320. Institute of Electrical and Electronics Engineers.
21. * D. Morales, L. Pardo, Igor Vajda: On the optimal number of classes in the Pearson goodness-of-fit tests. Kybernetika 41:6 (2005), 677-698. Ústav teorie informace a automatizace AV ČR, v. v. i..
22. * F. Liese, Igor Vajda: A general asymptotic theory of M-estimators II. Mathematical Methods of Statistics 13:1 (2004), 82-95.
23. * D. Morales, L. Pardo, M. C. Pardo, Igor Vajda: Rényi statistics for testing composite hypotheses in general exponential models. Statistics 38:2 (2004), 133-147.
24. * Igor Vajda, F. Öesterreicher: A new class of metric divergences on probability spaces and its applicability in statistics. Annals of the Institute of Statistical Mathematics 55:3 (2003), 639-653.
25. * D. Morales, L. Pardo, Igor Vajda: Asymptotic laws for disparity statistics in product multinomial models. Journal of Multivariate Analysis 85:3 (2003), 335-360. Elsevier.
26. * D. Morales, L. Pardo, M. C. Pardo, Igor Vajda: Limit laws for disparities of spacings. Journal of Nonparametric Statistics 15:3 (2003), 325-342. Taylor & Francis.
27. * M. C. Pardo, Igor Vajda: On asymptotic properties of information-theoretic divergences. IEEE Transactions on Information Theory 49:7 (2003), 1860-1868. Institute of Electrical and Electronics Engineers.
28. * Igor Vajda: Asymptotic laws for stochastic disparity statistics. Tatra Mountains Mathematical Publications 26:1 (2003), 1-12. Matematický ústav SAV.
29. * F. Liese, Igor Vajda: On square root of n-consistency and asymptotic normality of consistent estimators in models with independent observations. Rostocker Mathematisches Kolloquium 57:3 (2003), 3-51.
30. * A. M. Mayoral, D. Morales, J. Morales, Igor Vajda: On efficiency of estimation and testing with data quantized to fixed number of cells. Metrika 57:1 (2003), 1-27.
31. * Zdeněk Fabián, Igor Vajda: Core Functions and Core Divergences of Regular Distributions. Kybernetika 39:1 (2003), 29-42. Ústav teorie informace a automatizace AV ČR, v. v. i..   Download
32. * F. Liese, Igor Vajda: A general asymptotic theory of M-estimators I. Mathematical Methods of Statistics 12:4 (2003), 454-477.
33. * I. Molina, D. Morales, L. Pardo, Igor Vajda: On size increase for goodness of fit tests when observations are positively dependent. Statistics & Decisions 20:4 (2002), 399-414.
34. * A. Berlinet, Tomáš Hobza, Igor Vajda: Asymptotics for generalized piecewise linear histograms. Publications de l'Institut de Statistique de l'Universite de Paris 34:3 (2002), 3-19.
35. * A. Berlinet, Tomáš Hobza, Igor Vajda: Generalized piecewise linear histograms. Statistica Neerlandica 56:3 (2002), 301-313.
36. * Igor Vajda: On convergence of information contained in quantized observations. IEEE Transactions on Information Theory 48:8 (2002), 2163-2172. Institute of Electrical and Electronics Engineers.
37. * J. Beirlant, A. Berlinet, G. Biau, Igor Vajda: Divergence-type errors of smooth Barron-type density estimators. Test 11:1 (2002), 191-217.
38. * Igor Vajda, L. Gyorfi: Asymptotic distribution for goodness-of-fit statistics in a sequence of multinomial models. Statistics & Probability Letters 56:1 (2002), 57-67. Elsevier.
39. * M. D. Esteban, M. E. Castellanos, D. Morales, Igor Vajda: Monte Carlo comparison of four normality tests using different entropy estimates. Communications in Statistics - Simulation and Computation 30:4 (2001), 761-785. Taylor & Francis.
40. * Pavel Boček, T. Feglar, Martin Janžura, Igor Vajda: Prognosis and optimization of homogeneous Markov message handling networks. Kybernetika 37:6 (2001), 625-646. Ústav teorie informace a automatizace AV ČR, v. v. i..
41. * M. L. Menéndez, L. Pardo, Igor Vajda: Minimum disparity estimators for discrete and continuous models. Applications of Mathematics 46:6 (2001), 439-466. Springer.
42. * M. L. Menéndez, D. Morales, L. Pardo, Igor Vajda: Approximations to powers of phi-disparity goodness-of-fit tests. Communications in Statistics - Theory and Methods 30:1 (2001), 105-134. Taylor & Francis.
43. * Igor Vajda: Optimization of Barron density estimates under the chi-square criterion. Statistical Review 5:2 (2001), 395-396.
44. * A. Berlinet, Igor Vajda: Nonnegative piecewise linear histograms. Statistics 35:4 (2001), 295-317.
45. * M. L. Menéndez, D. Morales, L. Pardo, Igor Vajda: Minimum divergence estimators based on grouped data. Annals of the Institute of Statistical Mathematics 53:2 (2001), 277-288.
46. * J. Beirlant, L. Devroye, L. Györfi, Igor Vajda: Large deviations of divergence measures on partitions. Journal of Statistical Planning and Inference 93, 1-16. Elsevier.
47. * L. Györfi, Igor Vajda: A class of modified Pearson and Neyman statistics. Statistics & Decisions 19, 239-251.
48. * Igor Vajda, E. C. van der Meulen: Optimization of Barron density estimates. IEEE Transactions on Information Theory 47:5 (2001), 1867-1883. Institute of Electrical and Electronics Engineers.
49. * T. Hobza, Igor Vajda: On the Newcomb-Benford law in models of statistical data. Revista Mathématica Complutense 14:2 (2001), 1-13. Springer.
50. * D. Morales, L. Pardo, M. C. Pardo, Igor Vajda: Extension of the Wald statistic to models with dependent observations. Metrika 52:2 (2000), 97-113.
51. * Georges A. Darbellay, Igor Vajda: Entropy expressions for multivariate continuous distributions. IEEE Transactions on Information Theory 46:2 (2000), 709-712. Institute of Electrical and Electronics Engineers.
52. * A. Berlinet, F. Liese, Igor Vajda: Necessary and sufficient conditions for consistency of M-estimates in regression models with general errors. Journal of Statistical Planning and Inference 89, 243-267. Elsevier.
53. * D. Morales, L. Pardo, Igor Vajda: Rényi statistics in directed families of exponential experiments. Statistics 34:1 (2000), 151-174.
54. * Igor Vajda: On consistency of M-estimators in models with a linear substructure: Part 2. Discussiones Mathematicae 19:2 (1999), 375-392.
55. * Igor Vajda: On consistency of M-estimators in models with a linear substructure: Part 1. Discussiones Mathematicae 19:2 (1999), 355-373.
56. * Georges A. Darbellay, Igor Vajda: Estimation of the information by an adaptive partitioning of the observation space. IEEE Transactions on Information Theory 45:4 (1999), 1315-1321. Institute of Electrical and Electronics Engineers.
57. * F. Liese, Igor Vajda: M-estimators of structural parameters in pseudolinear models. Applications of Mathematics 44:4 (1999), 245-270. Springer.
58. * M. L. Menéndez, D. Morales, L. Pardo, Igor Vajda: Inference about stationary distributions of Markov chains based on divergences with observed frequencies. Kybernetika 35:3 (1999), 265-280. Ústav teorie informace a automatizace AV ČR, v. v. i..
59. * Igor Vajda, E. C. van der Meulen: The chi-square error of Barron estimator of regular density is asymptotically normal. Publications of the Institute of Statistics of the University of Paris 42, 93-110.
60. * A. Berlinet, Igor Vajda, E. C. van der Meulen: About the asymptotic accuracy of Barron density estimates. IEEE Transactions on Information Theory 44:3 (1998), 999-1009. Institute of Electrical and Electronics Engineers.
61. * Igor Vajda, Jiří Grim: About the maximum information and maximum likelihood principles in neural networks. Kybernetika 34:4 (1998), 485-494. Ústav teorie informace a automatizace AV ČR, v. v. i..
62. * Igor Vajda, B. Lonek, V. Nikolov, A. Veselý: Neural network realizations of Bayes decision rules for exponentially distributed data. Kybernetika 34:5 (1998), 497-514. Ústav teorie informace a automatizace AV ČR, v. v. i..
63. * L. Györfi, F. Liese, Igor Vajda, E. C. van der Meulen: Distribution estimates consistent in x2-divergence. Statistics 32, 31-57.
64. * Igor Vajda: Global information in statistical experiments and consistency of likelihood-based estimates and tests. Kybernetika 34:3 (1998), 245-263. Ústav teorie informace a automatizace AV ČR, v. v. i..
65. * M. L. Menéndez, D. Morales, L. Pardo, Igor Vajda: Two approaches to grouping of data and related disparity statistics. Communications in Statistics - Theory and Methods 27:3 (1998), 609-633. Taylor & Francis.
66. * Igor Vajda, E. C. van der Meulen: Global statistical information in exponential experiments and selection of exponential models. Applications of Mathematics 43:1 (1998), 23-51. Springer.
67. * M. L. Menéndez, D. Morales, L. Pardo, Igor Vajda: Asymptotic distributions of phi-divergences of hypothetical and observed frequencies on refined partitions. Statistica Neerlandica 52:1 (1998), 71-89.
68. * A. L. Rukhin, Igor Vajda: Change-point estimation as a nonlinear regression problem. Statistics 30, 181-200.
69. * Igor Vajda, Martin Janžura: On asymptotically optimal estimates for general observations. Stochastic Processes and their Applications 72:1 (1997), 27-45. Elsevier.
70. * Igor Vajda, A. Veselý: Perceptron approximations to Bayesian descrimination and classification of random signals. Neural Network World 3:4 (1997), 305-323. Ústav informatiky AV ČR, v. v. i..
71. * M. L. Menéndez, D. Morales, L. Pardo, Igor Vajda: Testing in stationary models based on divergences of observed and theoretical frequencies. Kybernetika 33:5 (1997), 465-475. Ústav teorie informace a automatizace AV ČR, v. v. i..
72. * D. Morales, L. Pardo, Igor Vajda: Some new statistics for testing hypotheses in parametric models. Journal of Multivariate Analysis 62:1 (1997), 137-168. Elsevier.
73. * M. C. Pardo, Igor Vajda: About distances of discrete distributions satisfying the data processing theorem of information theory. IEEE Transactions on Information Theory 43:4 (1997), 1288-1293. Institute of Electrical and Electronics Engineers.
74. * A. L. Rukhin, Igor Vajda: The error probability, entropy, and equivocation when the number of input messages increases. IEEE Transactions on Information Theory 42:6 (1996), 2228-2231. Institute of Electrical and Electronics Engineers.
75. * M. L. Menéndez, D. Morales, L. Pardo, Igor Vajda: About divergence-based goodness-of-fit tests in the Dirichlet-multinomial model. Communications in Statistics - Theory and Methods 25:5 (1996), 1119-1133. Taylor & Francis.
76. * L. Györfi, Igor Vajda, E. C. van der Meulen: Minimum Kolmogorov distances estimates for multivariate parametrized families. American Journal of Mathematical and Management Sciences 16, 167-191.
77. * D. Morales, L. Pardo, Igor Vajda: Divergence between various estimates of quantized information sources. Kybernetika 32:4 (1996), 395-407. Ústav teorie informace a automatizace AV ČR, v. v. i..
78. * L. Györfi, Igor Vajda, E. C. van der Meulen: Minimum Kolmogorov distance estimates of parameters and parametrized distributions. Metrika 43:3 (1996), 237-255.
79. * D. Morales, L. Pardo, Igor Vajda: Uncertainty of discrete stochastic systems: General theory and statistical inference. IEEE Transactions on Systems. Man and Cybernetics. Part A: Systems and Humans 26:6 (1996), 681-697.
80. * D. Morales, L. Pardo, Igor Vajda: Asymptotic divergence of estimates of discrete distributions. Journal of Statistical Planning and Inference 48:6 (1995), 347-369. Elsevier.
82. * M. L. Menéndez, D. Morales, L. Pardo, Igor Vajda: Divergence-based estimation and testing of statistical models of classification. Journal of Multivariate Analysis 52:2 (1995), 329-354. Elsevier.
83. * Igor Vajda: Statistical tests of optimality of source codes. Kybernetika 31:4 (1995), 321-330. Ústav teorie informace a automatizace AV ČR, v. v. i..
84. * Igor Vajda: Conditions equivalent to consistency of approximate MLE's for stochastic processes. Stochastic Processes and their Applications 56, 35-56. Elsevier.
85. * A. L. Rukhin, Igor Vajda: Adaptive decision making for stochastic processes. Journal of Statistical Planning and Inference 45, 313-329. Elsevier.
86. * Jarmila Kotásková, Igor Vajda, J. Kožený: Vzorce osobnosti II: Ontogenetické zvláštnosti vztahu morální úrovně a lokalizace kontroly. Československá psychologie 38:1 (1994), 15-27. Psychologický ústav AV ČR, v. v. i..
87. * Igor Vajda, F. Österreicher: Statistical analysis and applications of log-optimal investments. Kybernetika 30:3 (1994), 331-342. Ústav teorie informace a automatizace AV ČR, v. v. i..
88. * F. Liese, Igor Vajda: Consistency of M-estimates in general regression models. Journal of Multivariate Analysis 50:1 (1994), 93-114. Elsevier.
89. * L. Györfi, Igor Vajda, E. C. van der Meulen: Minimum Hellinger distance point estimates consistent under weak family regularity. Mathematical Methods of Statistics 3:1 (1994), 25-45.
90. * Jarmila Kotásková, J. Kožený, Igor Vajda: Vzorce osobnosti I: Interakce morální úrovně a lokalizace kontroly v sociálním kontextu. Československá psychologie 37:5 (1993), 385-397. Psychologický ústav AV ČR, v. v. i..
91. * Igor Vajda: Conditions equivalent and doubly equivalent to consistency of approximate MLE's. Journal of the Italian Statistical Society 2:1 (1993), 107-125.
92. * Jaroslava Feistauerová, Igor Vajda: Testing system entropy and prediction error probability. IEEE Transactions on Systems Man and Cybernetics 23:5 (1993), 1352-1358.
93. * H. Luschgy, A. L. Rukhin, Igor Vajda: Adaptive Tests for Stochastic Processes in the Ergodic Case. Stochastic Processes and their Applications 45:1 (1993), 45-59. Elsevier.
94. * F. Österreicher, Igor Vajda: Statistical Information and Discrimination. IEEE Transactions on Information Theory 39:3 (1993), 1036-1039. Institute of Electrical and Electronics Engineers.
95. * Igor Vajda, F. Österreicher: Existence, Uniqueness and Evaluation of Log-Optimal Investment Portfolio. Kybernetika 29:2 (1993), 105-120. Ústav teorie informace a automatizace AV ČR, v. v. i..
96. * M. Teboulle, Igor Vajda: Convergence of Best phi-Entropy Estimates. IEEE Transactions on Information Theory 39:1 (1993), 297-301. Institute of Electrical and Electronics Engineers.
97. * Otto Exner, Ivan Kramosil, Igor Vajda: Mathematical Evaluation of the Fit of a Theory with Experimental Data. Journal of Chemical Information and Computer Sciences 33:3 (1993), 407-411.
98. * Igor Vajda: Generalization of Discrimination-Rate Theorems of Chernoff and Stein. Kybernetika 26:4 (1990), 273-288.
99. * Igor Vajda: Distances and Discrimination Rates for Stochastic Processes. Stochastic Processes and their Applications 35:1 (1990), 47-57.
100. * Igor Vajda: Estimators Asymptotically Minimax in Wide Sense. Biometrical Journal 31:7 (1989), 803-810.
101. * Igor Vajda: About optimum signalling of information. Kybernetika 25:5 (1989), 175-199.
102. * Igor Vajda: Comparison of asymptotic variances for several estimators of location. Problems of Control and Information Theory 18:2 (1989), 79-89.
103. * Igor Vajda: Minimum-distance and gnostical estimators. Problems of Control and Information Theory 17:5 (1988), 253-266.

Conference papers (48)
2. * P. Harremoes, Igor Vajda: Efficiency of entropy testing. Proceedings ISIT 2008, 2639-2643. IEEE, Toronto 2008.   Download
3. * Igor Vajda, P. Harremoës: Entropy testing is efficient. Proceeding of ISIT 2007, 1841-1845. IEEE, Pistacewy 2007.
4. * Igor Vajda, E. van der Meulen: On estimation and testing by means of disparities based on m-spacings. Prague Stochastics 2006, 701-708. MATFYZPRESS, Praha 2006.
5. * Igor Vajda, Jana Zvárová: On relations between informations, entropies and Bayesian decisions. Prague Stochastics 2006, 709-718. MATFYZPRESS, Praha 2006.
6. * Igor Vajda: Asymptotics for Pearson-type goodness-of-fit statistics. Journées de Statistique de SFdS, 1-7. EDF, Clamart 2006.   Download
7. * Igor Vajda, Arnošt Veselý, Jana Zvárová: Models of information and knowledge for support of medical decision-making. Sborník semináře Informační technologie v péči o zdraví, 149-152. EuroMISE s.r.o., Praha 2004.
8. * D. Morales, L. Pardo, Igor Vajda: Digitalization of observations permits efficient estimation in continuos models. Soft Methodology and Random Information Systems, 315-322. Springer, Berlin 2004.
9. * Igor Vajda: On asymptotic equivalence of information-theoretic divergences. Proceedings 2001 IEEE International Symposium on Information Theory, 23. IEEE, Washington 2001.
10. * L. Györfi, G. Morvai, Igor Vajda: Information-theoretic methods in testing the goodness of fit. Proceedings of the 2000 IEEE International Symposium on Information Theory, 28. IEEE, New York 2000.
11. * Igor Vajda: About new communication networks technology and mathematics. Proceedings of the 4th Systems Science European Congress, 1011-1016. SESGE, Valencia 1999.
12. * Igor Vajda: Neural networks classification in exponential models with unknown statistics. Studies in Classification, Data Analysis, and Knowledge Organization. . Classification in the Information Age. Proceedings, 336-343. Springer, Berlin 1999.
13. * B. Hejna, Igor Vajda: Information transmission in stationary stochastic systems. Computing Anticipatory Systems. Proceedings, 405-417. American Institute of Physics, Woodbury 1999.
14. * M. L. Menéndez, D. Morales, L. Pardo, Igor Vajda: Minimum divergence estimation and testing in case of empirically quantized observations. Prague Stochastics '98. Proceedings, 391-396. JČMF, Praha 1998.
15. * A. Berlinet, F. Liese, Igor Vajda: M-estimates of parameters of periodic stochastic models. Prague Stochastics '98. Proceedings, 39-42. JČMF, Praha 1998.
16. * M. Kudrna, Igor Vajda: On log-optimal and Sharpe-Markowitz investment portfolios. Prague Stochastics '98. Proceedings, 331-336. JČMF, Praha 1998.
17. * D. Morales, L. Pardo, Igor Vajda: Divergence statistics for testing composite hypotheses. Prague Stochastics '98. Proceedings, 419-423. JČMF, Praha 1998.
18. * E. C. van der Meulen, Igor Vajda: About the chi-square error of Barron density estimate. Prague Stochastics '98. Proceedings, 557-562. JČMF, Praha 1998.
19. * Zdeněk Fabián, D. Morales, L. Pardo, Igor Vajda: Testing in Exponential Families by Means of the Rényi Distances. Prague Stochastics'98, 137-142. Union of Czech Mathematicians and Physicists, Prague 1998.
20. * Igor Vajda, Jiří Grim: About the maximum information and maximum likelihood principles in neural networks. Proceedings of the 1st IAPR TC1 Workshop on Statistical Techniques in Pattern Recognition, 189-197. ÚTIA AV ČR, Praha 1997.
21. * Igor Vajda: About perceptron realizations of Bayesian decisions. IEEE International Conference on Neural Networks, 253-257. IEEE, New York 1996.
22. * T. Feglar, Igor Vajda: Models of information networks with security services. Proceedings of the 1st International Conference on the Theory and Applications of Cryptology, 177-182. Czech Technical University, Prague 1996.
23. * Igor Vajda: Perceptron approximations to Bayesian decisions about random processes. Third European Congress on Systems Science, 989-992. Edizioni Kappa, Roma 1996.
24. * Igor Vajda, A. Veselý: Classification of random signals by neural networks. Proceedings of the 14th International Congress on Cybernetics, 102-106. Association Intern. de Cybernetique, Namur 1995.
25. * Martin Janžura, Igor Vajda: A sufficient condition for the consistency of parameter estimates. IEEE Information Theory Society. . Proceedings of the IEEE Information Theory Workshop, 9. IEEE, Poznan 1995.
26. * Igor Vajda: From perceptron to the Boltzman machine: Information processing by cognitive networks. Tercera Escuela Europea de Sistemas, 65-68. Universitat de Valencia, Valencia 1994.
27. * Igor Vajda, V. Kůs: Dimensionality reduction by projecting probability distributions on simple families. Computer-Intensive Methods in Control and Signal Processing, 53-61. ÚTIA AV ČR, Praha 1994.
28. * Igor Vajda: Approximate ML-estimates of random processes. Proceedings 1994 IEEE International Symposium on Information Theory, 436. IEEE, Piscataway 1994.
29. * L. Györfi, Igor Vajda, E. C. van der Meulen: Parameter estimation by projecting on structural statistical models. Asymptotic Statistics. Proceedings, 261-272. PhysicaVerlag, Heidelberg 1994.
30. * Igor Vajda: Conditions for consistency of MLE's. Asymptotic Statistics. Proceedings, 459-466. PhysicaVerlag, Heidelberg 1994.
31. * Igor Vajda: Stochastic System Optimization and Simulated Annealing. Second European Congress on Systems Science, 929-935. Afcet, Paris 1993.
32. * Igor Vajda, G. Morvai: A Survay on Log-Optimum Portfolio Selection. Second European Congress on Systems Science, 936-944. Afcet, Paris 1993.
33. * Igor Vajda: Maximum Likelihood Estimates and Entropy. Sixth Joint Swedish-Russian International Workshop on Information Theory, 425-428. Studentlitteratur, Lund 1993.
34. * Igor Vajda: Conditions for Consistency of Minimum Contrast Estimators and M-Estimators. Sborník prací letní školy JČMF ROBUST '92, 185-207. JČMF, Praha 1992.
35. * Igor Vajda: f-Divergences and Statistical Inference. Transactions of DISTANCIA '92, 405-408. Université Rennes, Rennes 1992.
36. * Igor Vajda: Qualitative and Quantitative Information in Systems. Second European School of Systems Science, 321-328. AFCET, Paris 1992.
37. * L. Györfi, Igor Vajda, E. C. van der Meulen: Family of Point Estimates Yielded by L1-Consistent Density Estimate. International Conference on L1-Statistical Analysis and Related Methods, 415-430. Elsevier, Amsterdam 1992.
38. * Igor Vajda: Consistent Estimation of Distributions from Polish Spaces Using Minimum Distance. Transactions of the Eleventh Prague Conference on Information Theory, Statistical Decision Functions, Random Processes, 423-427. Academia, Prague 1992.
39. * Igor Vajda: Asymptotic Rényi Distances and the Problem of Signal Detection. Proceedings of the IEEE Symposium on Information Theory, 72-73. IEEE, New York 1991.
40. * Igor Vajda: Asymptotic Rényi Distances. Mathematische Stochastik, 19. Mathematisches Forschungsinstitut, Oberwolfach 1990.
41. * Igor Vajda, J. Přibyl: Error Statistics in Data Networks. Transactions of COMNET '90, 95-104. J.von Neumann, Budapest 1990.
42. * Igor Vajda: Teorie informace a teleinformatika. Projektování a provoz systémů teleinformatiky, 170-175. ČSVTS, Brno 1990.
43. * Igor Vajda, Jiří Michálek: Statistical Applications of Rényi Distances. Robustness and Nonparametric Statistics. Proceedings, 151-152. Banach Center, Warszawa 1989.
44. * Igor Vajda: Distances of Stochastic Processes and their Statistical Applications. Robustness and Mathematical Statistics, 231-232. Banach Internat.Mathem.Center, Warszawa 1989.
45. * Igor Vajda: Rate of Discrimination Between Random Processes and Fields. PROBASTAT '89. Zborník príspevkov, 134-135. VVTŠ, Liptovský Mikuláš 1989.
46. * Jiří Nedoma, Igor Vajda: Komprese řečového signálu na nízkou úroveň rychlosti přenosu informace. Analýza, syntéza a rozpoznávání řeči, 3-11. ČSVTSFELČVUT, Praha 1989.
47. * Igor Vajda: Rate of Discrimination Between Random Processes and Fields. 5. Vilnius International Conference on Probability Theory and Mathematical Statistics, 202-203. Institut matematiki i kybernetiki, Vilnius 1989.
48. * Igor Vajda: F-projection of o-finite measures and its information-theoretic and statistical applications. Transactions of the 10. Prague Conference on Information Theory, Statistical Decision Functions, Random Processes, 381-388. Academia, Praha 1988.

Other publications (88)
1. * Pavel Boček, Igor Vajda, Edward van der Meulen: Asymptotic properties and numerical comparison of spacings-based power divergence statistics. Abstracts of Contributions to 6th International Workshop on Data – Algorithms – Decision Making, 26-26. ÚTIA AV ČR, Praha 2010.   Download
2. * Pavel Boček, Igor Vajda, E. van der Meulen: Goodness-of-Fit Disparity Statistics Obtained by Hypothetical and Empirical Quantizations. Research Report 2292. , Praha 2010.   Download
3. * Pavel Boček, Igor Vajda, E. van der Meulen: Asymptotic properties and numerical comparison of spacings-based power divergence statistics. Prague Stochastics 2010, Book of Abstracts, 65-65. Institute of Information Theory and Automation, Prague 2010.
4. * Igor Vajda, Edward van der Meulen: Divergences between models and data under hypothetical and empirical quantizations. Research Report 2275. ÚTIA AV ČR, v.v.i, Praha 2010.   Download
5. * D. Morales, Igor Vajda: Generalized information criteria for optimal Bayes decisions. Research Report 2274. ÚTIA AV ČR, v.v.i, Praha 2010.   Download
6. * P. Harremoes, Igor Vajda: Evaluation of tight bounds for divergences. Research Report 2273. ÚTIA AV ČR v.v.i, Praha 2010.   Download
7. * Igor Vajda: Information theory models for clinical decision support. 30th Annual Conference of the International Society for Clinical Biostatistics, 117-117. Ústav informatiky AV ČR, v.v.i, Praha 2009.   Download
8. * W. Stummer, Igor Vajda: Bergman distances in exponential families. Abstracts of Contributions to 5th International Workshop on Data-Algorthms-Decision Making, 14-14. UTIA, AV ČR, v.v.i, Praha 2009.   Download
9. * Igor Vajda, W. Stummer: On Bregman distances and divergences of probability measures. Interní publikace DAR-ÚTIA 2009/2. ÚTIA AV ČR, v.v.i, Praha 2009.   Download
10. * M. Broniatowski, Igor Vajda: Several applications of divergence criteria in continuous families. Research Report 2257. ÚTIA AV ČR v.v.i, Praha 2009.   Download
11. * A. Berlinet, Igor Vajda: Extensions of a Devroye-Lugosi theorem. Research Report 2240. ÚTIA AV ČR, Praha 2008.   Download
12. * Igor Vajda, E. C. van der Meulen: Asymptotic properties of spacings-based divergence statistics. Research Report 2241. ÚTIA AV ČR, Praha 2008.   Download
13. * Igor Vajda, D. Morales: Generalized information criteria for optimal Bayes decisions. Research Report 2239. ÚTIA AV ČR, Praha 2008.   Download
14. * Igor Vajda: Maximum likelihood in the context of more general minimum distance methods. Zimní workshop matematické statistiky. Program a abstrakty, 8-8. Ústav teórie merania SAV, Bratislava 2008.
15. * Igor Vajda, W. Stummer: Bregman distances in exponential families of probability distributions. Interní publikace DAR - ÚTIA 2008/7. ÚTIA AV ČR, Praha 2008.   Download
16. * Igor Vajda: Modifications of divergence criteria in continuous families. Research Report 2230. ÚTIA AV ČR, Praha 2008.   Download
17. * A. Berlinet, Igor Vajda: Divergence Criteria for Improved Selection Rules. Interní publikace DAR - ÚTIA 2008/5. ÚTIA AV ČR, Praha 2008.   Download
18. * Igor Vajda: On Efficiencies of Decisions about Statistical Models Based on f-divergences of Empirical Distributions. Interní publikace DAR - ÚTIA 2008/4. ÚTIA AV ČR, Praha 2008.   Download
19. * Igor Vajda: On efficiencies of decisions about statistical models based on f-divergences of empirical distributions. Sborník Abstraktů pro ROBUST 2008, 51-51. Matfyzz press, Praha 2008.   Download
20. * Igor Vajda: Divergence-based statistical decisions. Information and Communication Conference, Abstracts, 12-13. A. Renyi Institute, Hungarian Acaddemy of Sciences, Budapest 2008.   Download
21. * Igor Vajda, P. Harremoës: Consistency of various divergence statistics. Research Report 2218. ÚTIA AV ČR, Praha 2008.
22. * P. Harremoës, Igor Vajda: Efficiency of Entropy Testing. Intrení publikace DAR-ÚTIA 2008/2. ÚTIA AV ČR, Praha 2008.
23. * D. Morales, Igor Vajda: Generalized Informations and Bayesian Errors. Interní publikace DAR - ÚTIA 2007/18. ÚTIA AV ČR, Praha 2007.
24. * Pavel Boček, Igor Vajda: Testování hypotéz o násobných multinomiálních modelech. Interní publikace DAR - ÚTIA 2007/15. ÚTIA AV ČR, Praha 2007.
25. * W. Stummer, Igor Vajda: On Divergences of Finite Measures and their Statistical Applicability. Interní publikace DAR - ÚTIA 2007/14. ÚTIA AV ČR, Praha 2007.
26. * Igor Vajda: Limit Laws for f-disparity Statistics under Local Alternatives. Interní publikace DAR – ÚTIA 2007/11. ÚTIA AV ČR, Praha 2007.
27. * Igor Vajda: O divergenci a fluktuaci proměnných veličin a pravděpodobnostních distribucí. Interní publikace DAR – ÚTIA 2007/10. ÚTIA AV ČR, Praha 2007.
28. * Igor Vajda: Application of Phi-divergence to Estimation in Continuous Families. Interní publikace DAR - ÚTIA 2007/8. ÚTIA AV ČR, Praha 2007.
29. * W. Stummer, Igor Vajda: On Divergences of Finite Measures and Their Applications in Censoring. Interní publikace DAR - ÚTIA 2007/7. ÚTIA AV ČR, Praha 2007.
30. * Igor Vajda, P. Harremoës: Efficient Testing of Uniformity using Power Divergence Statistics. Interní publikace DAR - ÚTIA 2007/4. ÚTIA AV ČR, Praha 2007.
31. * V. Kůs, D. Morales, Igor Vajda: Extensions of the Parametric Families of Divergences Used in Statistical Inference. Interní publikace DAR - ÚTIA 2007/2.. ÚTIA AV ČR, Praha 2007.
32. * Tomáš Hobza, L. Pardo, Igor Vajda: Robust Median Estimator in Logistic Regression. Interní publikace - DAR - ÚTIA 2006/31. ÚTIA AV ČR, Praha 2006.
33. * Igor Vajda, Jana Zvárová: Some Results on Generalized Entropies with Applications in Bayesian Decisions a Biometry. Interní publikace - DAR - ÚTIA 2006/29. ÚTIA AV ČR, Praha 2006.
34. * Igor Vajda, Jana Zvárová: Some relations between informations and entropies with applications in Bayesian decisions and biometry. Interní publikace - DAR - ÚTIA 2006/17. ÚTIA AV ČR, Praha 2006.
35. * F. Liese, Igor Vajda: Divergences and their applications in sufficiency, deficiency and testing of hypotheses. Interní publikace - DAR - ÚTIA 2006/16. ÚTIA AV ČR, Praha 2006.
36. * Tomáš Hobza, Igor Vajda, E. C. van der Meulen: Consistent estimation and testing by means of disparity statistics based on m-spacings. Interní publikace - DAR - ÚTIA 2006/15. ÚTIA AV ČR, Praha 2006.
37. * Igor Vajda, E. C. van der Meulen: Goodness-of-fit testing based on hypothetical and empirical quantizations. Interní publikace - DAR - ÚTIA 2006/14. ÚTIA AV ČR, Praha 2006.
38. * Igor Vajda: On two types of phi-divergence goodness-of-fit statistics. Interní publikace - DAR - ÚTIA 2006/13. ÚTIA AV ČR, Praha 2006.
39. * Igor Vajda: On asymptotic distributions of f-disparity statistics under local alternatives. Research Report 2169. ÚTIA AV ČR, Praha 2006.
40. * Igor Vajda: Divergence pravděpodobnostních distribucí a statistická informace. Research Report 2168. ÚTIA AV ČR, Praha 2006.
41. * Igor Vajda, E. van der Meulen: Goodness-of-fit tests based on observations quantized by hypothetical and empirical quantiles. Research Report 2160. ÚTIA AV ČR, Praha 2006.
42. * Igor Vajda: Divergence-Based Extension of the Maximum Likehood Method. Interní publikace - DAR - ÚTIA 2006/10. ÚTIA AV ČR, Praha 2006.
43. * F. Liese, Igor Vajda: On Divergences and their new Applications in Statistics and Information Theory. Interní publikace - DAR - ÚTIA 2006/12. ÚTIA AV ČR, Praha 2006.
44. * F. Liese, Igor Vajda: On Divergence and Informations in Statistics and Information Theory. ÚTIA AV ČR, Praha 2005.
45. * Jana Zvárová, Igor Vajda: On Genetic Information and Diversity. ISCB26, 50. University of Szeged, Szeged 2005.
46. * Tomáš Marek, Igor Vajda, Karel Vrbenský: Minimum divergence adaptation of bivariate distributions. Interní publikace - DAR - ÚTIA 2005/44. ÚTIA AV ČR, Praha 2005.
47. * T. Hobza, L. Pardo, Igor Vajda: Robust Median Estimators in General Logistic Regression. Interní publikace - DAR - ÚTIA 2005/40. ÚTIA AV ČR, Praha 2005.
48. * W. Stummer, Igor Vajda: Optimal Statistical Decision About Some Alternative Financial Models. Interní publikace - DAR - ÚTIA 2005/35. ÚTIA AV ČR, Praha 2005.
49. * D. Morales, L. Pardo, Igor Vajda: On Efficient Estimation in Continuous Models Based on Finitely Quantized Observations. Interní publikace - DAR - ÚTIA 2005/27. ÚTIA AV ČR, Praha 2005.
50. * Pavel Boček, Tomáš Marek, Igor Vajda: Discrete Efficient Methods 1: Testing Compound Hypotheses. Interní publikace - DAR - ÚTIA 2005/15. ÚTIA AV ČR, Praha 2005.
51. * A. Berlinet, Igor Vajda: On Asymptotic Sufficiency and Optimality of Quantizations. Interní publikace - DAR - ÚTIA 2005/18. ÚTIA AV ČR, Praha 2005.
52. * Tomáš Hobza, L. Pardo, Igor Vajda: Median Estimators of Parameters of Logistic Regression in Models with Discrete or Continuous Responses. Research Report 2124. ÚTIA AV ČR, Praha 2004.
53. * M. C. Pardo, L. Pardo, Igor Vajda: Testing Homogeneity of Independent Samples from Arbitrary Models. Research Report 2104. ÚTIA AV ČR, Praha 2004.
54. * Jana Zvárová, Igor Vajda: On Genetic Information, Diversity and Distance. International Joint Meeting EuroMISE 2004 Proceedings, 16. EuroMISE, Prague 2004.
55. * F. Liese, Igor Vajda: On Consistency and Asymptotic Normality of Consistent Estimators in Models with Independent Observations. Research Report 2042. ÚTIA AV ČR, Praha 2002.
56. * Igor Vajda, E. C. van der Meulen: On minimum divergence adaptation of bivariate distributions to given marginals. Abstract. Abstracts of the 24th European Meeting of Statisticians & 14th Prague Conference on Information Theory, Statistical Decision Functions and Random Processes, 344. Institute of Information Theory and Automation, Prague 2002.
57. * Zdeněk Fabián, Igor Vajda: Core Functions and Core Divergences of Regular Distributions. Technical Report V-863. ICS AS CR, Prague 2002.
58. * F. Liese, Igor Vajda: First Order Theory of M-estimators in General Models with Independent Observations. Research Report 2017. ÚTIA AV ČR, Praha 2001.
59. * Zdeněk Fabián, Igor Vajda: Core Distance of Probability Distributions. Technical Report V-812. ICS AS CR, Prague 2001.
60. * Tomáš Hobza, Igor Vajda, Karel Vrbenský: Estimation of Distribution in Telecommunication Networks and its Optimization. Research Report 2001. ÚTIA AV ČR, Praha 2000.
61. * T. Feglar, Igor Vajda, Martin Janžura: Optimal Design of Communication Networks. Research Report 1978. ÚTIA AV ČR, Praha 1999.
62. * L. Györfi, G. Morvai, Igor Vajda: Asymptotic Results for Iformation-Theoretic and Statistical Criteria of Goodness of Fit. Research Report 1961. ÚTIA AV ČR, Praha 1999.
63. * F. Liese, Igor Vajda: A General Asymptotic Theory of M-Estimators. Research Report 1951. ÚTIA AV ČR, Praha 1999.
64. * A. Berlinet, T. Hobza, Igor Vajda: Analysis of Some New Histogram Based Estimators. Research Report 98-09. Université Montpellier, Montpellier 1998.
65. * Igor Vajda: On Consistency of M-estimators in Models with a Linear Substructure. Research Report 1931. ÚTIA AV ČR, Praha 1998.
66. * T. Hobza, V. Kůs, Igor Vajda, E. C. van der Meulen, K. Vrbenský: Optimal Partitions and Dominating Distributions for Barron Density Estimates. Research Report 1928. ÚTIA AV ČR, Praha 1998.
67. * D. Morales, L. Pardo, Igor Vajda: Testing Simple and Composite Hypotheses in Convergent Exponential Families. Research Report 1922. ÚTIA AV ČR, Praha 1998.
68. * Georges A. Darbellay, Igor Vajda: Estimation of the Mutual Information with Data-dependent Partitions. Research Report 1921. ÚTIA AV ČR, Praha 1998.
69. * Georges A. Darbellay, Igor Vajda: Entropy Expressions for Continuous Multivariate Distributions. Research Report 1920. ÚTIA AV ČR, Praha 1998.
70. * M. L. Menéndez, D. Morales, L. Pardo, Igor Vajda: About Parametric Estimation and Testing Based on Sample Quantiles. Research Report 1899. ÚTIA AV ČR, Praha 1997.
71. * V. Kůs, Igor Vajda: Asymptotic Formulas and Density Estimates for Call Admission Control. Research Report 1891. ÚTIA AV ČR, Praha 1996.
72. * Igor Vajda, V. Kůs: Adaptive Density Estimates for ATM Networks. Research Report 1893. ÚTIA AV ČR, Praha 1996.
73. * V. Kůs, Igor Vajda: A Comparative Study of Nonparametric Density Estimates. Research Report 1892. ÚTIA AV ČR, Praha 1996.
74. * Igor Vajda, Jiří Grim: About Optimality of Probabilistic Basic Function Neural Networks. Research Report 1887. ÚTIA AV ČR, Praha 1996.
75. * E. C. van der Meulen, Igor Vajda: Nonparametric density estimates consistent in x2-divergence. World Congress of the Bernoulli Society. Abstracts, 464. Bernoulli Society, Vienna 1996.
76. * D. Morales, L. Pardo, Igor Vajda: About the Behaviour of Rényi's Divergence Statistics under Null Composite Hypotheses. Research Report 1870. ÚTIA AV ČR, Praha 1996.
77. * Igor Vajda, Jiří Grim: On Information Theoretic Optimality of Radial Basis Function Neural Networks. Research Report 1864. ÚTIA AV ČR, Praha 1996.
78. * Igor Vajda, V. Kůs: Relations Between Divergences, Total Variations and Euclidean Distances. Research Report 1853. ÚTIA AV ČR, Praha 1995.
79. * Igor Vajda: Information-Theoretic Methods in Statistics. Research Report 1834. ÚTIA AV ČR, Praha 1995.
80. * M. L. Menéndez, D. Morales, L. Pardo, Igor Vajda: About Phi-Divergence Goodness-of-Fit Tests in the Dirichlet-Multinomial Model. Research Report 1846. ÚTIA AV ČR, Praha 1995.
81. * M. Teboulle, Igor Vajda: Convergence of Best phí-Entropy Estimates. Research Report 91-22. University of Maryland, Baltimore 1991.
82. * F. Liese, A. L. Rukhin, Igor Vajda: Consistent Estimation in the Case of Regression Data Fields. ÚTIA ČSAV, Praha 1991.
83. * Igor Vajda, F. Liese: Asymptotic Normality of M-estimators in Nonlinear Regression. ÚTIA ČSAV, Praha 1991.
84. * Igor Vajda, F. Liese: Consistency of M-estimators in Nonlinear Regression. ÚTIA ČSAV, Praha 1991.
85. * Jaroslava Feistauerová, Jaroslav Vacík, Igor Vajda: Výzkum úsporného zápisu kódové knihy do paměti a programy pro počítače řady PC/PX. ÚTIA ČSAV, Praha 1989.
86. * Igor Vajda: Alfa-odhady polohy. ÚTIA ČSAV, Praha 1989.
87. * Igor Vajda: Error prevention as an alternative to error correction. ÚTIA ČSAV, Praha 1989.
88. * Jaroslava Feistauerová, Igor Vajda: Kódová kniha 88-1 a její komprimovaný zápis do paměti počítače. ÚTIA ČSAV, Praha 1988.