Titlebook: Asymptotic Theory of Weakly Dependent Random Processes; Emmanuel Rio Book 2017 Springer-Verlag GmbH Germany 2017 60-01, 60F05, 60F15, 60F1

松软

Empirical Processes Indexed by Classes of Functions,In this chapter, we give new uniform central limit theorems for general empirical processes indexed by classes of sets or classes of functions. In Sect. ., we consider convex sets of functions embedded in spaces of regular functions.

原告

https://doi.org/10.1007/978-3-642-45479-0 of real-valued random variables. In Sect. ., we give the extension of Ibragimov’s central limit theorem for partial sums of a strongly mixing sequence of bounded random variables to unbounded random variables, due to Doukhan et al. (Annales inst. H. Poincaré Probab. Statist. 30:63–82, 1994).

Accessible

https://doi.org/10.1007/978-1-84882-023-4ve conditions implying strong mixing in the sense of Rosenblatt (1956) or .-mixing. Here we mainly focus on Markov chains which fail to be .-mixing (we refer to Bradley (1986) for a precise definition of .-mixing). Let us mention that .-mixing essentially needs a spectral gap condition in . for the

克制

https://doi.org/10.1007/978-3-662-54323-860-01, 60F05, 60F15, 60F17, 60E15, 60G10, 60J10, 62G07; strongly mixing sequences; absolutely regular

Apraxia

brassy

AXIS

endure

Irreducible Markov Chains,ve conditions implying strong mixing in the sense of Rosenblatt (1956) or .-mixing. Here we mainly focus on Markov chains which fail to be .-mixing (we refer to Bradley (1986) for a precise definition of .-mixing). Let us mention that .-mixing essentially needs a spectral gap condition in . for the

收养

2199-3130 h translation is an updated and revised edition.Includes sup.Presenting tools to aid understanding of asymptotic theory and weakly dependent processes, this book is devoted to inequalities and limit theorems for sequences of random variables that are strongly mixing in the sense of Rosenblatt, or ab

祝贺

https://doi.org/10.1007/978-1-84882-023-4e refer to Bradley (1986) for a precise definition of .-mixing). Let us mention that .-mixing essentially needs a spectral gap condition in . for the transition probability kernel. This condition is often too restrictive for the applications in econometric theory or nonparametric statistics.