Ultra High Dimensional Change Point Detection

by   Xin Liu, et al.

Structural breaks have been commonly seen in applications. Specifically for detection of change points in time, research gap still remains on the setting in ultra high dimension, where the covariates may bear spurious correlations. In this paper, we propose a two-stage approach to detect change points in ultra high dimension, by firstly proposing the dynamic titled current correlation screening method to reduce the input dimension, and then detecting possible change points in the framework of group variable selection. Not only the spurious correlation between ultra-high dimensional covariates is taken into consideration in variable screening, but non-convex penalties are studied in change point detection in the ultra high dimension. Asymptotic properties are derived to guarantee the asymptotic consistency of the selection procedure, and the numerical investigations show the promising performance of the proposed approach.



There are no comments yet.


page 1

page 2

page 3

page 4


Some Clustering-based Change-point Detection Methods Applicable to High Dimension, Low Sample Size Data

Detection of change-points in a sequence of high-dimensional observation...

A Generalized Knockoff Procedure for FDR Control in Structural Change Detection

Controlling false discovery rate (FDR) is crucial for variable selection...

Change-point detection in dynamic networks via graphon estimation

We propose a general approach for change-point detection in dynamic netw...

A unified framework for correlation mining in ultra-high dimension

An important problem in large scale inference is the identification of v...

On Posterior consistency of Bayesian Changepoint models

While there have been a lot of recent developments in the context of Bay...

Multi-threshold Change Plane Model: Estimation Theory and Applications in Subgroup Identification

We propose a multi-threshold change plane regression model which natural...

Multiscale change point detection via gradual bandwidth adjustment in moving sum processes

A method for the detection of changes in the expectation in univariate s...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.