Skip to main content

A Uniform Functional Law of the Logarithm for a Local Gaussian Process

  • Conference paper
High Dimensional Probability III

Part of the book series: Progress in Probability ((PRPR,volume 55))

Abstract

We establish a uniform functional law of the logarithm for a Gaussian process closely related to the local empirical process. We then discuss the necessity of the polynomial covering assumption on the indexing class of functions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. K.S. AlexanderRates of growth and sample moduli for weighted empirical processes. Probab. Th. Rel. Fields 75 (1987), 379–423.

    Article  MATH  Google Scholar 

  2. M. ArconesThe large deviation principle of stochastic processes. I. Theor. Probab. Appl.47 (2002a). In press.

    Google Scholar 

  3. M. ArconesThe large deviation principle of stochastic processes. II.Theor. Probab. Appl. 47 (2002b). In press.

    Google Scholar 

  4. M. Csörgö and P. RévészHow big are the increments of the Wiener process?Ann. Probab. 7 (1979), 731–737.

    Article  MathSciNet  MATH  Google Scholar 

  5. M. Csörgö and P. RévészStrong Approximations in Probability and Statistics. Academic Press, New York, 1981.

    MATH  Google Scholar 

  6. P. DeheuvelsFunctional laws of the iterated logarithm for large increments of empirical and quantile processes. Stoch. Proc. Appl.43 (1992), 133–163

    Article  MathSciNet  MATH  Google Scholar 

  7. P. Deheuvels and D.M. MasonFunctional laws of the iterated logarithm for increments of empirical and quantile processes. Ann. Probab. 20 (1992), 1248–1287.

    Article  MathSciNet  MATH  Google Scholar 

  8. P. Deheuvels and D.M. MasonFunctional laws of the iterated logarithm for local empirical processes indexed by sets. Ann. Probab. 22 (1994), 1619–1661.

    Article  MathSciNet  MATH  Google Scholar 

  9. L. Devroye and G. LugosiCombinatorial Methods in Density Estimation. Springer, New York, 2000.

    Google Scholar 

  10. R. M. DudleyUniform Central Limit TheoremsCambridge University Press, New York, 1999.

    Book  MATH  Google Scholar 

  11. U. Einmahl and D.M. MasonGaussian approximation of local empirical processes indexed by functions. Probab. Th. Rel. Fields 107 (1997), 283–311.

    Article  MathSciNet  MATH  Google Scholar 

  12. U. Einmahl and D.M. MasonStrong approximations for local empirical processes. In: Progress in Probability 43, Proceedings of High Dimensional Probability, Oberwolfach 1996(E. Eberlein, M. Hahn and J. Kuelbs, eds.), pp. 75–92, Birkhäuser, Basel, 1998.

    Google Scholar 

  13. U. Einmahl and D.M. MasonAn empirical process approach to the uniform consistency of kernel—type function estimators. J. Theoretical Prob. 13 (2000), 1–37.

    Article  MathSciNet  MATH  Google Scholar 

  14. E. Giné and A. GuillouRates of strong consistency for multivariate kernel density estimators. Ann. Inst. H. Poincaré. 38 (2002), 907–921.

    Article  MATH  Google Scholar 

  15. E. Giné, V. Koltchinskii and J. Wellner, Ratio limit theorems for empirical processes. Preprint.

    Google Scholar 

  16. K. ItôMultiple Wiener integral. J. Math. Soc. Japan 3 (1951),157–169.

    Article  MathSciNet  MATH  Google Scholar 

  17. J. Komlós, P. Major and G. TusnádyAn approximation of partial sums of independent rv’s and the sample df I. Z. Wahrsch. verw. Gebiete. 32 (1975), 111–131.

    Article  MATH  Google Scholar 

  18. J. Komlós, P. Major and G. TusnádyAn approximation of partial sums of independent rv’s and the sample df II. Z. Wahrsch. verw. Gebiete. 34 (1976), 33–58.

    Article  MATH  Google Scholar 

  19. M. Ledoux and M. Talagrand, Probability in Banach Spaces, Springer, New York, 1991.

    MATH  Google Scholar 

  20. D.M. MasonA strong invariance theorem for the tail empirical process. Ann. Inst. H. Poincaré 24 (1988), 491–506.

    MATH  Google Scholar 

  21. D.M. Mason, A Uniform functional law of the logarithm for the local empirical process. Preprint.

    Google Scholar 

  22. D.M. Mason, G.R. Shorack and J.A. WellnerStrong limit theorems for the oscillation moduli of the uniform empirical process. Z. Wahrsch. verw. Gebiete 65 (1983), 83–97.

    Article  MathSciNet  MATH  Google Scholar 

  23. C. MuellerA unification of Strassen’s law and Levy’s modulus of continuity. Z.Wahrsch. 56 (1981), 163–179.

    Article  MathSciNet  MATH  Google Scholar 

  24. D. Nolan and J.S. MarronUniform consistency of automatic and location—adaptive delta—sequence estimators. Probab. Th. Rel. Fields 80 (1989), 619–632.

    Article  MathSciNet  MATH  Google Scholar 

  25. D. Nolan and D. PollardU—processes: rates of convergence. Ann. Statist. 15 (1987), 780–799.

    Article  MathSciNet  MATH  Google Scholar 

  26. E. ParzenAn approach to time series analysis. Ann. Math. Statist. 32 (1961), 951–989.

    Article  MathSciNet  MATH  Google Scholar 

  27. P. RévészA generalization of Strassen’s functional law of the iterated logarithm. Wahrsch. verw. Gebiete. 50 (1979), 257–264.

    Article  MathSciNet  MATH  Google Scholar 

  28. E. RioLocal invariance principles and their applications to density estimation. Probab. Th. Rel. Fields 98 (1994), 21–45.

    Article  MathSciNet  MATH  Google Scholar 

  29. G.R. Shorack and J.A. WellnerEmpirical Processes with Applications to Statistics. Wiley1986.

    Google Scholar 

  30. E.M. SteinSingular Integrals and Differentiability Properties of Functions. Princeton University Press, Princeton, New Jersey, 1970.

    MATH  Google Scholar 

  31. W. StuteThe oscillation behavior of empirical processes. Ann. Probab. 10 (1982a), 86–107.

    Article  MathSciNet  MATH  Google Scholar 

  32. W. StuteThe law of the iterated logarithm for kernel density estimators. Ann. Probab. 10 (1982b), 414–422.

    Article  MathSciNet  MATH  Google Scholar 

  33. W. StuteThe oscillation behavior of empirical processes: the multivariate case. Ann. Probab. 12 (1984), 361–379.

    Article  MathSciNet  MATH  Google Scholar 

  34. M. TalagrandSharper bounds for Gaussian and empirical processes. Ann. Probab. (1994), 28–76.

    Google Scholar 

  35. A.W. van der Vaart and J.A. Wellner, Weak Convergence and Empirical Processes. Springer, New York, 1996.

    MATH  Google Scholar 

  36. A.Yu ZaitsevEstimates of the Lévy—Prokhorov distance in the multivariate central limit theorem for random variables with finite exponential moments. Theory Probab. Appl. 31 (1987a), 203–220.

    Article  Google Scholar 

  37. A.Yu ZaitsevOn the Gaussian approximation of convolutions under multidimensional analogues of S. N. Bernstein’s inequality conditions. Probab. Th. Rel. Fields 74 (1987b), 534–566.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer Basel AG

About this paper

Cite this paper

Mason, D.M. (2003). A Uniform Functional Law of the Logarithm for a Local Gaussian Process. In: Hoffmann-Jørgensen, J., Wellner, J.A., Marcus, M.B. (eds) High Dimensional Probability III. Progress in Probability, vol 55. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-8059-6_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-0348-8059-6_9

  • Publisher Name: Birkhäuser, Basel

  • Print ISBN: 978-3-0348-9423-4

  • Online ISBN: 978-3-0348-8059-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics