The Annals of Statistics

The Empirical Process of some Long-Range Dependent Sequences with an Application to $U$-Statistics

Herold Dehling and Murad S. Taqqu

Full-text: Open access

Abstract

Let $(X_j)^\infty_{j = 1}$ be a stationary, mean-zero Gaussian process with covariances $r(k) = EX_{k + 1} X_1$ satisfying $r(0) = 1$ and $r(k) = k^{-D}L(k)$ where $D$ is small and $L$ is slowly varying at infinity. Consider the two-parameter empirical process for $G(X_j),$ $\bigg\{F_N(x, t) = \frac{1}{N} \sum^{\lbrack Nt \rbrack}_{j = 1} \lbrack 1\{G(X_j) \leq x\} - P(G(X_1) \leq x) \rbrack; // -\infty < x < + \infty, 0 \leq t \leq 1\bigg\},$ where $G$ is any measurable function. Noncentral limit theorems are obtained for $F_N(x, t)$ and they are used to derive the asymptotic behavior of some suitably normalized von Mises statistics and $U$-statistics based on the $G(X_j)$'s. The limiting processes are structurally different from those encountered in the i.i.d. case.

Article information

Source
Ann. Statist. Volume 17, Number 4 (1989), 1767-1783.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
http://projecteuclid.org/euclid.aos/1176347394

Digital Object Identifier
doi:10.1214/aos/1176347394

Mathematical Reviews number (MathSciNet)
MR1026312

Zentralblatt MATH identifier
0696.60032

JSTOR
links.jstor.org

Subjects
Primary: 60F17: Functional limit theorems; invariance principles
Secondary: 62G30: Order statistics; empirical distribution functions

Keywords
von Mises statistics $U$-statistics Hermite polynomials empirical process long-range dependence

Citation

Dehling, Herold; Taqqu, Murad S. The Empirical Process of some Long-Range Dependent Sequences with an Application to $U$-Statistics. Ann. Statist. 17 (1989), no. 4, 1767--1783. doi:10.1214/aos/1176347394. http://projecteuclid.org/euclid.aos/1176347394.


Export citation