Abstract
The paper considers random processes with values in a vector Skorokhod space; i.e., in a product of a finite numberĀ of Skorokhod spaces. Our interest is focused on weak convergence of a sequence of such processes. Particularly, we present a criterion for weak convergence in vector Skorokhod spaces. The idea is based on an embedding of a vector Skorokhod space into a Skorokhod space. Also, an illustrative example of two empirical processes is attached.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bickel, P.J., Wichura, M.S.: Convergence criteria for multiparameter stochastic processes and some applications. Ann. Math. Statist. 42, 1656ā1670 (1971)
Billingsley, P.: Convergence of Probability Measures. Wiley, New York (1968)
Ferger, D., Vogel, D.: Weak convergence of the empirical process and the rescaled empirical distribution function in the Skorokhod product space. Teor. Veroyatnost. i Primenen. 54(4), 750ā770 (2009). https://doi.org/10.4213/tvp3538
Neuhaus, G.: On weak convergence of stochastic processes with multidimensional time parameter. Ann. Math. Stat. 42, 1285ā1295 (1971)
Skorokhod, A.V.: Limit theorems for stochastic processes. Theory Probab. Appl. 1(1), 289ā319 (1956)
Straf, M.L.: Weak convergence of stochastic processes with several parameters. In: Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics and Probability, vol. 2, pp. 187ā222 (1972)
Acknowledgements
The author is thankful to anonymous referee for his comments and suggestions helping to improve the text.
The research was supported by the Czech Science Foundation (GA ÄR) under the project 18-05631S.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
Ā© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Lachout, P. (2019). A Criterion for Weak Convergence in Vector Skorokhod Spaces. In: Steland, A., RafajÅowicz, E., Okhrin, O. (eds) Stochastic Models, Statistics and Their Applications. SMSA 2019. Springer Proceedings in Mathematics & Statistics, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-030-28665-1_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-28665-1_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-28664-4
Online ISBN: 978-3-030-28665-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)