A review on minimax rates in change point detection and localisation
Y Yu - arXiv preprint arXiv:2011.01857, 2020 - arxiv.org
This paper reviews recent developments in fundamental limits and optimal algorithms for
change point analysis. We focus on minimax optimal rates in change point detection and …
change point analysis. We focus on minimax optimal rates in change point detection and …
High dimensional change point inference: Recent developments and extensions
B Liu, X Zhang, Y Liu - Journal of multivariate analysis, 2022 - Elsevier
Change point analysis aims to detect structural changes in a data sequence. It has always
been an active research area since it was introduced in the 1950s. In modern statistical …
been an active research area since it was introduced in the 1950s. In modern statistical …
Central limit theorems for high dimensional dependent data
Central limit theorems for high dimensional dependent data Page 1 Bernoulli 30(1), 2024,
712–742 https://doi.org/10.3150/23-BEJ1614 Central limit theorems for high dimensional …
712–742 https://doi.org/10.3150/23-BEJ1614 Central limit theorems for high dimensional …
Offline change detection under contamination
In this work, we propose a non-parametric and robust change detection algorithm to detect
multiple change points in time series data under non-adversarial contamination. The …
multiple change points in time series data under non-adversarial contamination. The …
Adversarially robust change point detection
Change point detection is becoming increasingly popular in many application areas. On one
hand, most of the theoretically-justified methods are investigated in an ideal setting without …
hand, most of the theoretically-justified methods are investigated in an ideal setting without …
Robust mean change point testing in high-dimensional data with heavy tails
We study a mean change point testing problem for high-dimensional data, with
exponentially-or polynomially-decaying tails. In each case, depending on the $\ell_0 $-norm …
exponentially-or polynomially-decaying tails. In each case, depending on the $\ell_0 $-norm …
Robust change-point detection for functional time series based on U-statistics and dependent wild bootstrap
L Wegner, M Wendler - Statistical Papers, 2024 - Springer
The aim of this paper is to develop a change-point test for functional time series that uses the
full functional information and is less sensitive to outliers compared to the classical CUSUM …
full functional information and is less sensitive to outliers compared to the classical CUSUM …
Robust inference for change points in high dimension
This paper proposes a new test for a change point in the mean of high-dimensional data
based on the spatial sign and self-normalization. The test is easy to implement with no …
based on the spatial sign and self-normalization. The test is easy to implement with no …
Robust Estimation of High-Dimensional Linear Regression with Changepoints
The identification of changes in linear models is a fundamental problem encountered in
various applications. Traditional methods often encounter difficulties when attempting to …
various applications. Traditional methods often encounter difficulties when attempting to …
Likelihood asymptotics in nonregular settings: A review with emphasis on the likelihood ratio
AR Brazzale, V Mameli - Statistical Science, 2024 - projecteuclid.org
Likelihood Asymptotics in Nonregular Settings: A Review with Emphasis on the Likelihood
Ratio Page 1 Statistical Science 2024, Vol. 39, No. 2, 322–345 https://doi.org/10.1214/23-STS910 …
Ratio Page 1 Statistical Science 2024, Vol. 39, No. 2, 322–345 https://doi.org/10.1214/23-STS910 …