A review on minimax rates in change point detection and localisation
arXiv:2011.01857
Abstract
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 localisation, in both parametric and nonparametric models. We start with the univariate mean change point analysis problem and review the state-of-the-art results in the literature. We then move on to more complex data types and investigate general principles behind the optimal procedures that lead to minimax rate-optimal results.
References in corpus (10)
- Change-point detection in panel data via double CUSUM statistic
- The screening and ranking algorithm to detect DNA copy number variations
- Multiscale inference about a density
- Testing for changes in polynomial regression
- Optimal nonparametric change point detection and localization
- A log-linear time algorithm for constrained changepoint detection
- Multiple Changepoint Estimation in High-Dimensional Gaussian Graphical Models
- Change-point detection for multivariate and non-Euclidean data with local dependency
- Element-wise estimation error of a total variation regularized estimator for change point detection
- On a phase transition in general order spline regression