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.
Similar content being viewed by others
References
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)
Arcones, M.A.: Limit theorems for nonlinear functionals of a stationary Gaussian sequence of vectors. Ann. Probab. 22(4), 2242–2274 (1994)
Aue, A., Berkes, I., Horváth, L.: Selection from a stable box. Bernoulli 14(1), 125–139 (2008)
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)
Berkes, I., Horváth, L., Schauer, J.: Asymptotic behavior of trimmed sums. Stoch. Dyn. 12(1), 1150002 (2012)
Berkes, I., Philipp, W.: Approximation theorems for independent and weakly dependent random vectors. Ann. Probab. 7(1), 29–54 (1979)
Bickel, P.J., Wichura, M.J.: Convergence criteria for multiparameter stochastic processes and some applications. Ann. Math. Stat. 42, 1656–1670 (1971)
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)
Bougerol, P., Picard, N.: Strict stationarity of generalized autoregressive processes. Ann. Probab. 20(4), 1714–1730 (1992)
Bradley, R.C.: Introduction to Strong Mixing Conditions, vol. 1. Kendrick Press, Heber City (2007)
Brockwell, P.J., Davis, R.A.: Time Series: Theory and Methods. Springer Series in Statistics, 2nd edn. Springer, New York (1991)
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)
Dedecker, J., Doukhan, P.: A new covariance inequality and applications. Stoch. Process. Appl. 106(1), 63–80 (2003)
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)
Dedecker, J., Prieur, C.: New dependence coefficients. Examples and applications to statistics. Probab. Theory Relat. Fields 132(2), 203–236 (2005)
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)
Dehling, H.: A note on a theorem of Berkes and Philipp. Z. Wahrsch. Verw. Gebiete 62(1), 39–42 (1983)
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)
Dehling, H., Philipp, W.: Almost sure invariance principles for weakly dependent vector-valued random variables. Ann. Probab. 10(3), 689–701 (1982)
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)
Doukhan, P., Wintenberger, O.: An invariance principle for weakly dependent stationary general models. Probab. Math. Stat. 27(1), 45–73 (2007)
Dudley, R.M.: Distances of probability measures and random variables. Ann. Math. Stat. 39(5), 1563–1572 (1968)
Eberlein, E.: An invariance principle for lattices of dependent random variables. Z. Wahrsch. Verw. Gebiete 50(2), 119–133 (1979)
Eberlein, E.: Strong approximation of very weak Bernoulli processes. Z. Wahrsch. Verw. Gebiete 62(1), 17–37 (1983)
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)
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)
Hannan, E.J.: Multiple Time Series. Wiley, New York (1970)
Hannan, E.J.: Central limit theorems for time series regression. Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete 26, 157–170 (1973)
Hariz, S.B.: Uniform clt for empirical process. Stoch. Process. Appl. 115(2), 339–358 (2005)
Huskova, M.: Tests and estimators for the change point problem based on M-statistics. Stat. Risk Model. 14(2), 115–136 (1996)
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)
Kallenberg, O.: Foundations of Modern Probability. Probability and its Applications (New York), 2nd edn. Springer, New York (2002)
Karatzas, I., Shreve, S.E.: Brownian motion and stochastic calculus, volume 113 of graduate texts in mathematics, 2nd edn. Springer, New York (1991)
Kuelbs, J., Philipp, W.: Almost sure invariance principles for partial sums of mixing \(B\)-valued random variables. Ann. Probab. 8(6), 1003–1036 (1980)
Levental, S.: A uniform clt for uniformly bounded families of martingale differences. J. Theor. Probab. 2(3), 271–287 (1989)
Mandelbrot, B.: New methods in statistical economics. J. Political Econ. 71, 421 (1963)
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)
Merlevède, F., Peligrad, M., Utev, S.: Recent advances in invariance principles for stationary sequences. Probab. Surv. 3, 1–36 (2006). ( electronic)
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)
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)
Philipp, W.: Weak and \(L^{p}\)-invariance principles for sums of \(B\)-valued random variables. Ann. Probab. 8(1), 68–82 (1980)
Rio, E.: Processus empiriques absolument réguliers et entropie universelle. Probab. Theory Relat. Fields 111(4), 585–608 (1998)
Tsay, R.S.: Analysis of Financial Time Series. Wiley Series in Probability and Statistics Wiley-Interscience, 2nd edn. Wiley, Hoboken (2005)
van der Vaart, A.W.: Asymptotic statistics. Cambridge University Press, Cambridge (1998)
Wu, W.B.: Nonlinear system theory : another look at dependence. Proc Natl Acad Sci USA 102, 14150–14154 (2005)
Wu, W.B.: Strong invariance principles for dependent random variables. Ann. Probab. 35(6), 2294–2320 (2007)
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
Corresponding author
Rights and permissions
About this article
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
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10959-016-0670-z