Skip to main content
Log in

On Weak Invariance Principles for Partial Sums

  • Published:
Journal of Theoretical Probability Aims and scope Submit manuscript

Abstract

Given a sequence of random functionals \(\bigl \{X_k(u)\bigr \}_{k \in \mathbb {Z}}\), \(u \in \mathbf{I}^d\), \(d \ge 1\), the normalized partial sums \(\check{S}_{nt}(u) = n^{-1/2}\bigl (X_1(u) + \cdots + X_{\lfloor n t \rfloor }(u)\bigr )\), \(t \in [0,1]\) and its polygonal version \({S}_{nt}(u)\) are considered under a weak dependence assumption and \(p > 2\) moments. Weak invariance principles in the space of continuous functions and càdlàg functions are established. A particular emphasis is put on the process \(\check{S}_{nt}(\widehat{\theta })\), where \(\widehat{\theta } \xrightarrow {\mathbb {P}} \theta \), and weaker moment conditions (\(p = 2\) if \(d = 1\)) are assumed.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Andrews, D.W.K., Pollard, D.: An introduction to functional central limit theorems for dependent stochastic processes. Int. Stat. Rev. / Revue Internationale de Statistique 62(1), 119–132 (1994)

  2. Arcones, M.A.: Limit theorems for nonlinear functionals of a stationary Gaussian sequence of vectors. Ann. Probab. 22(4), 2242–2274 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  3. Aue, A., Berkes, I., Horváth, L.: Selection from a stable box. Bernoulli 14(1), 125–139 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  4. Berkes, I., Hörmann, S., Horváth, L.: The functional central limit theorem for a family of GARCH observations with applications. Stat. Probab. Lett. 78(16), 2725–2730 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  5. Berkes, I., Horváth, L., Schauer, J.: Asymptotic behavior of trimmed sums. Stoch. Dyn. 12(1), 1150002 (2012)

  6. Berkes, I., Philipp, W.: Approximation theorems for independent and weakly dependent random vectors. Ann. Probab. 7(1), 29–54 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  7. Bickel, P.J., Wichura, M.J.: Convergence criteria for multiparameter stochastic processes and some applications. Ann. Math. Stat. 42, 1656–1670 (1971)

    Article  MathSciNet  MATH  Google Scholar 

  8. Billingsley P.: Convergence of probability measures. Wiley series in probability and statistics: probability and statistics. A Wiley-Interscience Publication, 2nd edn. Wiley, New York (1999)

  9. Bougerol, P., Picard, N.: Strict stationarity of generalized autoregressive processes. Ann. Probab. 20(4), 1714–1730 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  10. Bradley, R.C.: Introduction to Strong Mixing Conditions, vol. 1. Kendrick Press, Heber City (2007)

    MATH  Google Scholar 

  11. Brockwell, P.J., Davis, R.A.: Time Series: Theory and Methods. Springer Series in Statistics, 2nd edn. Springer, New York (1991)

  12. Csörgő, M., Horváth, L.: Limit theorems in change-point analysis. Wiley series in probability and statistics. Wiley, Chichester (1997) ( With a foreword by David Kendall)

  13. Dedecker, J., Doukhan, P.: A new covariance inequality and applications. Stoch. Process. Appl. 106(1), 63–80 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  14. Dedecker, J., Doukhan, P., Lang, G., León, R., Louhichi, S., Prieur, C.l.: Weak dependence: with examples and applications, volume 190 of Lecture Notes in Statistics. Springer, New York (2007)

  15. Dedecker, J., Prieur, C.: New dependence coefficients. Examples and applications to statistics. Probab. Theory Relat. Fields 132(2), 203–236 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  16. Dehling, H.: Limit theorems for sums of weakly dependent banach space valued random variables. Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete 63(3), 393–432 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  17. Dehling, H.: A note on a theorem of Berkes and Philipp. Z. Wahrsch. Verw. Gebiete 62(1), 39–42 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  18. Dehling, H., Durieu, O., Tusche, M.: A sequential empirical clt for multiple mixing processes with application to \({\cal{B}}\)-geometrically ergodic markov chains. Electron. J. Probab. 19(86), 1–26 (2014)

    MathSciNet  MATH  Google Scholar 

  19. Dehling, H., Philipp, W.: Almost sure invariance principles for weakly dependent vector-valued random variables. Ann. Probab. 10(3), 689–701 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  20. Doukhan, P., Massart, P., Rio, E.: Invariance principles for absolutely regular empirical processes. Annales de l’institut Henri Poincaré (B) Probabilités et Statistiques 31(2), 393–427 (1995)

  21. Doukhan, P., Wintenberger, O.: An invariance principle for weakly dependent stationary general models. Probab. Math. Stat. 27(1), 45–73 (2007)

    MathSciNet  MATH  Google Scholar 

  22. Dudley, R.M.: Distances of probability measures and random variables. Ann. Math. Stat. 39(5), 1563–1572 (1968)

    Article  MathSciNet  MATH  Google Scholar 

  23. Eberlein, E.: An invariance principle for lattices of dependent random variables. Z. Wahrsch. Verw. Gebiete 50(2), 119–133 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  24. Eberlein, E.: Strong approximation of very weak Bernoulli processes. Z. Wahrsch. Verw. Gebiete 62(1), 17–37 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  25. Ghose, D., Kroner, K.F.: The relationship between garch and symmetric stable processes: finding the source of fat tails in financial data. J. Empir. Finance 2(3), 225–251 (1995)

    Article  Google Scholar 

  26. Haas, M., Pigorsch, C.: Financial economics, fat-tailed distributions. In: Meyers, RobertA (ed.) Encyclopedia of Complexity and Systems Science, pp. 3404–3435. Springer, Berlin (2009)

    Chapter  Google Scholar 

  27. Hannan, E.J.: Multiple Time Series. Wiley, New York (1970)

    Book  MATH  Google Scholar 

  28. Hannan, E.J.: Central limit theorems for time series regression. Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete 26, 157–170 (1973)

    Article  MathSciNet  MATH  Google Scholar 

  29. Hariz, S.B.: Uniform clt for empirical process. Stoch. Process. Appl. 115(2), 339–358 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  30. Huskova, M.: Tests and estimators for the change point problem based on M-statistics. Stat. Risk Model. 14(2), 115–136 (1996)

    MathSciNet  MATH  Google Scholar 

  31. Jacod, J., Shiryaev, A.N.: Limit theorems for stochastic processes, volume 288 of Grundlehren der Mathematischen Wissenschaften [fundamental principles of mathematical sciences], 2nd edn. Springer, Berlin (2003)

  32. Kallenberg, O.: Foundations of Modern Probability. Probability and its Applications (New York), 2nd edn. Springer, New York (2002)

  33. Karatzas, I., Shreve, S.E.: Brownian motion and stochastic calculus, volume 113 of graduate texts in mathematics, 2nd edn. Springer, New York (1991)

  34. Kuelbs, J., Philipp, W.: Almost sure invariance principles for partial sums of mixing \(B\)-valued random variables. Ann. Probab. 8(6), 1003–1036 (1980)

    Article  MathSciNet  MATH  Google Scholar 

  35. Levental, S.: A uniform clt for uniformly bounded families of martingale differences. J. Theor. Probab. 2(3), 271–287 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  36. Mandelbrot, B.: New methods in statistical economics. J. Political Econ. 71, 421 (1963)

    Article  Google Scholar 

  37. Marcus, M.B., Philipp, W.: Almost sure invariance principles for sums of \(B\)-valued random variables with applications to random Fourier series and the empirical characteristic process. Trans. Am. Math. Soc. 269(1), 67–90 (1982)

    MathSciNet  MATH  Google Scholar 

  38. Merlevède, F., Peligrad, M., Utev, S.: Recent advances in invariance principles for stationary sequences. Probab. Surv. 3, 1–36 (2006). ( electronic)

  39. Peligrad, M., Utev, S.: Invariance principle for stochastic processes with short memory. In: High dimensional probability, volume 51 of IMS Lecture Notes Monogr. Ser., pp. 18–32. Inst. Math. Statist., Beachwood (2006)

  40. Philipp, W.: Almost sure invariance principles for sums of \(B\)-valued random variables. In: Probability in Banach spaces, II (Proc. Second Internat. Conf., Oberwolfach, 1978), volume 709 of Lecture Notes in Math., pp. 171–193. Springer, Berlin (1979)

  41. Philipp, W.: Weak and \(L^{p}\)-invariance principles for sums of \(B\)-valued random variables. Ann. Probab. 8(1), 68–82 (1980)

    Article  MathSciNet  MATH  Google Scholar 

  42. Rio, E.: Processus empiriques absolument réguliers et entropie universelle. Probab. Theory Relat. Fields 111(4), 585–608 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  43. Tsay, R.S.: Analysis of Financial Time Series. Wiley Series in Probability and Statistics Wiley-Interscience, 2nd edn. Wiley, Hoboken (2005)

  44. van der Vaart, A.W.: Asymptotic statistics. Cambridge University Press, Cambridge (1998)

    Book  MATH  Google Scholar 

  45. Wu, W.B.: Nonlinear system theory : another look at dependence. Proc Natl Acad Sci USA 102, 14150–14154 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  46. Wu, W.B.: Strong invariance principles for dependent random variables. Ann. Probab. 35(6), 2294–2320 (2007)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgments

I would like to thank the anonymous reviewer for the many comments and suggestions. The generous help has been of major benefit.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Moritz Jirak.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jirak, M. On Weak Invariance Principles for Partial Sums. J Theor Probab 30, 703–728 (2017). https://doi.org/10.1007/s10959-016-0670-z

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10959-016-0670-z

Keywords

Mathematics Subject Classification (2010)

Navigation