Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generalized linear statistics for near epoch dependent processes with
  application to EGARCH-processes   The class of Generalized $L$-statistics ($GL$-statistics) unifies a broad
class of different estimators, for example scale estimators based on
multivariate kernels. $GL$-statistics are functionals of $U$-quantiles and
therefore the dimension of the kernel of the $U$-quantiles determines the
kernel dimension of the estimator. Up to now only few results for multivariate
kernels are known. Additionally, most theory was established under independence
or for short range dependent processes. In this paper we establish a central
limit theorem for $GL$-statistics of functionals of short range dependent data,
in particular near epoch dependent sequences on absolutely regular processes,
and arbitrary dimension of the underlying kernel. This limit theorem is based
on the theory of $U$-statistics and $U$-processes, for which we show a central
limit theorem as well as an invariance principle. The use of near epoch
dependent processes admits us to consider functionals of short range dependent
processes and therefore models like the EGARCH-model. We also develop a
consistent estimator of the asymptotic variance of $GL$-statistics.

26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
27
The categories of this paper are: comp-gas
1
The categories of this paper are: cs
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn