Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimal Sequential Kernel Detection for Dependent Processes   In many applications one is interested to detect certain (known) patterns in
the mean of a process with smallest delay. Using an asymptotic framework which
allows to capture that feature, we study a class of appropriate sequential
nonparametric kernel procedures under local nonparametric alternatives. We
prove a new theorem on the con- vergence of the normed delay of the associated
sequential detection procedure which holds for dependent time series under a
weak mixing condition. The result suggests a simple procedure to select a
kernel from a finite set of candidate kernels, and therefore may also be of
interest from a practical point of view. Further, we provide two new theorems
about the existence and an explicit representation of optimal kernels
minimizing the asymptotic normed delay. The results are illustrated by some
examples.

8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
1
The categories of this paper are: cs
10
The categories of this paper are: q-bio
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin
27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
26
The categories of this paper are: bayes-an