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Theory of Probability and Mathematical Statistics

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Some applications of the Gnedenko–Korolyuk method to empirical distributions


Authors: E. O. Lutsenko, O. V. Marinich and I. K. Matsak
Translated by: O. I. Klesov
Journal: Theor. Probability and Math. Statist. 78 (2009), 133-146
MSC (2000): Primary 60B12
DOI: https://doi.org/10.1090/S0094-9000-09-00767-4
Published electronically: August 4, 2009
MathSciNet review: 2446854
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Abstract | References | Similar Articles | Additional Information

Abstract: A new proof of the Kolmogorov theorem on the asymptotic behavior of the deviation between a theoretical and an empirical distribution function is presented. We use the Gnedenko–Korolyuk approach based on some combinatorial properties of the merged sample constructed from two other independent samples. Some statistical applications of the Gnedenko–Korolyuk theorem are discussed.


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References
  • A. Kolmogorov, Sulla determinazione empirica di una legge di distribuzione, Giorn. Ist. Ital. Attuari 4 (1933), no. 1, 83–91.
  • N. V. Smirnov, Teoriya veroyatnosteĭ i matematicheskaya statistika. Izbrannye trudy, Izdat. “Nauka”, Moscow, 1970 (Russian). Commentaries by D. M. Čibisov, V. K. Zaharov, O. V. Sarmanov, E. S. Kedrova, M. A. Rybinskaja and L. N. Bol′šev. MR 0265117
  • B. V. Gnedenko and V. S. Korolyuk, On the maximum discrepancy between two empirical distributions, Doklady Akad. Nauk SSSR (N.S.) 80 (1951), 525–528 (Russian). MR 0045357
  • V. S. Korolyuk, On the discrepancy of empiric distributions for the case of two independent samples, Izv. Akad. Nauk SSSR. Ser. Math. 19 (1955), 81–96 (Russian). MR 0067418
  • J. L. Doob, Heuristic approach to the Kolmogorov-Smirnov theorems, Ann. Math. Statistics 20 (1949), 393–403. MR 30732, DOI https://doi.org/10.1214/aoms/1177729991
  • Peter Gänssler and Winfried Stute, Empirical processes: a survey of results for independent and identically distributed random variables, Ann. Probab. 7 (1979), no. 2, 193–243. MR 525051
  • M. Csörgő and P. Révész, Strong approximations in probability and statistics, Probability and Mathematical Statistics, Academic Press, Inc. [Harcourt Brace Jovanovich, Publishers], New York-London, 1981. MR 666546
  • È. V. Khmaladze, Some applications of the theory of martingales in statistics, Uspekhi Mat. Nauk 37 (1982), no. 6(228), 193–212 (Russian). MR 683280
  • Patrick Billingsley, Convergence of probability measures, John Wiley & Sons, Inc., New York-London-Sydney, 1968. MR 0233396
  • E. J. G. Pitman, Some basic theory for statistical inference, Chapman and Hall, London; A Halsted Press Book, John Wiley & Sons, New York, 1979. Monographs on Applied Probability and Statistics. MR 549771
  • I. I. Gikhman and A. V. Skorokhod, Teoriya sluchaĭ nykh protsessov. Tom I, Izdat. “Nauka”, Moscow, 1971 (Russian). MR 0341539
  • B. V. Gnedenko, Theory of Probability, Sixth edition, Nauka, Moscow, 1988; English. transl., Gordon and Breach Science Publishers Newark, NJ, 1997.
  • Paul Schmid, On the Kolmogorov and Smirnov limit theorems for discontinuous distribution functions, Ann. Math. Statist. 29 (1958), 1011–1027. MR 101582, DOI https://doi.org/10.1214/aoms/1177706438
  • A. A. Borovkov, Matematicheskaya statistika, “Nauka”, Moscow, 1984 (Russian). Otsenka parametrov. Proverka gipotez. [Estimation of parameters. Testing of hypotheses]. MR 782295

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Additional Information

E. O. Lutsenko
Affiliation: Department of Operation Research, Faculty for Cybernetics, National Taras Shevchenko University, Academician Glushkov Avenue 6, Kyiv 03127, Ukraine
Email: ievgen_lutsenko@ukr.net

O. V. Marinich
Affiliation: Department of Operation Research, Faculty for Cybernetics, National Taras Shevchenko University, Academician Glushkov Avenue 6, Kyiv 03127, Ukraine
Email: marinich@voliacable.com

I. K. Matsak
Affiliation: Department of Operation Research, Faculty for Cybernetics, National Taras Shevchenko University, Academician Glushkov Avenue 6, Kyiv 03127, Ukraine
Email: mik@unicyb.kiev.ua

Keywords: Empirical distribution function, Kolmogorov theorem, Gnedenko–Korolyuk method
Received by editor(s): July 2, 2007
Published electronically: August 4, 2009
Article copyright: © Copyright 2009 American Mathematical Society