Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Inference for Multiple Change-points in Linear and Non-linear Time
  Series Models   In this paper we develop a generalized likelihood ratio scan method (GLRSM)
for multiple change-points inference in piecewise stationary time series, which
estimates the number and positions of change-points and provides a confidence
interval for each change-point. The computational complexity of using GLRSM for
multiple change-points detection is as low as $O(n(\log n)^3)$ for a series of
length $n$. Consistency of the estimated numbers and positions of the
change-points is established. Extensive simulation studies are provided to
demonstrate the effectiveness of the proposed methodology under different
scenarios.

33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
17
The categories of this paper are: q-fin