Summary
For a probability measure P let P n be its empirical measures. The main result is that if there are constants C and γ such that for all P, all suitably measurable Vapnik-Cervonenkis classes C of index 1 containing the empty set and all M ≥ 1, we have
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References
Adler, R. J. (1990). An Introduction to Continuity, Extrema and Related Topics for General Gaussian Processes. IMS Lecture Note and Monograph Series 12.
Adler, R. J., Brown, L. D. (1986). Tail behaviour for suprema of empirical processes. Ann. Probab. 14 1–30.
Adler, R. J., Samorodnitsky, G. (1987). Tail behaviour for the suprema of Gaussian processes with applications to empirical processes. Ann. Probab. 15 1339–1351.
Alexander, K. S. (1982). Some limit theorems and inequalities for weighted and non-identically distributed empirical processes. Ph. D. dissertation, Mathematics, Massachusetts Institute of Technology.
Alexander, K. S. (1984). Probability inequalities for empirical processes and a law of the iterated logarithm. Ann. Probab. 12 1041–1067. Correction: 15 428-430 (1987).
Assouad, Patrice (1983). Densité et dimension. Ann. Inst. Fourier (Grenoble) 33 no. 3, 233–282.
Cabaña, E. M. (1984). On the transition density of multidimensional parameter Wiener process with one barrier. J. Appl. Prob. 21 197–200.
Cabaña, E. M., Wschebor, M. (1982). The two-parameter Brownian bridge: Kolmogorov inequalities and upper and lower bounds for the distribution of the maximum. Ann. Probab. 10 289–302.
Devroye, L. (1982). Bounds for the uniform deviation of empirical measures. J. Multivar. Analysis 12 72–79.
Dudley, R. M. (1973). Sample functions of the Gaussian process. Ann. Probab. 1 66–103.
Dudley, R. M. (1978). Central limit theorems for empirical measures. Ann. Probab. 6 899–929; Correction, 7 909-911 (1979).
Dudley, R. M. (1984). A course on empirical processes. Ecole d’été de probabilitiés de St.-Flour, 1982. Lect. Notes Math. (Springer) 1097 1–142.
Dudley, R. M. (1985) The structure of some Vapnik-Červonenkis classes. In: Le Cam, L. M., Olshen, R. A. (eds.). Proceedings of the Berkeley Conference in Honor of Jerzy Neyman and Jack Kiefer, 1983, 2, 495–508. Wadsworth, Monterey, California.
Dudley, R. M. (1989). Real Analysis and Probability. Brooks/Cole and Wads-worth, Belmont, Calif.
Dvoretzky, A., Kiefer, J., Wolfowitz, J. (1956). Asymptotic minimax character of the sample distribution function and of the classical multinomial estimator. Ann. Math. Stat. 27 642–669.
Goodman, V. (1976). Distribution estimates for functionals of the two-parameter Wiener process. Ann. Probab. 4 977–982.
Haussler, David (1991). Sphere packing numbers for subsets of the Boolean n-cube with bounded Vapnik-Chervonenkis dimension. Univ. Calif. Santa Cruz Computer Research Lab. Tech. Report UCSC-CRL-91-41.
Kiefer, J. (1961). On large deviations of the empiric d.f. of vector chance variables and a law of the iterated logarithm. Pacific J. Math. 11 649–660.
Kolmogorov, A. N. (1933). Sulla determinazione empirica di una legge di distribuzione. Giorn. Istit. Ital. Attuari 4 83–91.
Leadbetter, M. R., Lindgren, G., and Rootzén, H. (1983). Extremes and Related Properties of Random Sequences and Processes. Springer, New York.
Lévy, P. (1965). Processus stochastiques et mouvement brownien, 2d. ed. (1st ed. 1948). Gauthier-Villars, Paris.
Massart, P. (1983). Vitesses de convergence dans le théorème central limite pour des processus empiriques. C. R. Acad. Sci. Paris 296 Sér. I, 937–940.
Massart, P. (1986). Rates of convergence in the central limit theorem for empirical processes. Ann. Inst. Henri Poincaré (Prob.-Stat.) 22 381–423, also in: X. Fernique, B. Heinkel, M. B. Marcus, P. A. Meyer (eds.) Geometrical and Statistical Aspects of Probability in Banach Spaces. Proceedings, Strasbourg, 1985. Lect. Notes Math. (Springer) 1193 73-109 (1986).
Pickands, James III (1969). Upcrossing probabilities for stationary Gaussian processes. Trans. Amer. Soc. 145 51–73.
Ruben, H. (1961). Probability content of regions under spherical normal distributions, III: the Divariate normal integral. Ann. Math. Statist. 32 171–186.
Samorodnitsky, Gennady (1991). Probability tails of Gaussian extrema. Stochastic Processes Applies. 38, 55–84.
Smith, D. L. (1985). Vapnik-Červonenkis classes and the supremum distribution of a Gaussian process. Ph.D. dissertation, Mathematics, Massachusetts Institute of Technology.
Talagrand, M. (1992). Sharper bounds for empirical processes (preprint).
Vapnik, V. N., Červonenkis, A. Ya. (1968). Uniform convergence of frequencies of occurrences of events to their probabilities. Sov. Math. Dokl. 9 915–918.
Vapnik, V. N., Červonenkis, A. Ya. (1971). On the uniform convergence of relative frequences of events to their probabilities. Theory Prob. Appl. 16 264–280.
Wenocur, R. S., Dudley, R. M. (1981). Some special Vapnik-Chervonenkis classes. Discrete Math. 33 313–318.
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Smith, D.L., Dudley, R.M. (1992). Exponential Bounds in Vapnik-Červonenkis Classes of Index 1. In: Dudley, R.M., Hahn, M.G., Kuelbs, J. (eds) Probability in Banach Spaces, 8: Proceedings of the Eighth International Conference. Progress in Probability, vol 30. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4612-0367-4_31
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