Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Valid Post-Detection Inference for Change Points Identified Using Trend
  Filtering   There are many research works and methods about change point detection in the
literature. However, there are only a few that provide inference for such
change points after being estimated. This work mainly focuses on a statistical
analysis of change points estimated by the PRUTF algorithm, which incorporates
trend filtering to determine change points in piecewise polynomial signals.
This paper develops a methodology to perform statistical inference, such as
computing p-values and constructing confidence intervals in the newly developed
post-selection inference framework. Our work concerns both cases of known and
unknown error variance. As pointed out in the post-selection inference
literature, the length of such confidence intervals are undesirably long. To
resolve this shortcoming, we also provide two novel strategies, global
post-detection, and local post-detection which are based on the intrinsic
properties of change points. We run our proposed methods on real as well as
simulated data to evaluate their performances.

33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
28
The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
29
The categories of this paper are: funct-an
3
The categories of this paper are: physics
35
The categories of this paper are: mtrl-th