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We propose an algorithm for nonparametric online change point detection based on sequential score function estimation and the tracking the best expert approach. The core of the procedure is a version of the fixed share forecaster tailored…

Machine Learning · Computer Science 2026-02-18 Anna Markovich , Nikita Puchkin

The problem of quantifying uncertainty about the locations of multiple change points by means of confidence intervals is addressed. The asymptotic distribution of the change point estimators obtained as the local maximisers of moving sum…

Methodology · Statistics 2022-06-20 Haeran Cho , Claudia Kirch

Sudden changes are ubiquitous in nature. Identifying them is of crucial importance for a number of applications in medicine, biology, geophysics, and social sciences. Here we investigate the problem in the quantum domain, considering a…

Quantum Physics · Physics 2016-10-12 Gael Sentís , Emilio Bagan , John Calsamiglia , Giulio Chiribella , Ramon Munoz-Tapia

The quickest change detection problem is considered in the context of monitoring large-scale independent normal distributed data streams with possible changes in some of the means. It is assumed that for each individual local data stream,…

Statistics Theory · Mathematics 2016-03-18 Yuan Wang , Yajun Mei

We consider the offline change point detection and localization problem in the context of piecewise stationary networks, where the observable is a finite sequence of networks. We develop algorithms involving some suitably modified CUSUM…

In a physical system, changing parameters such as temperature can induce a phase transition: an abrupt change from one state of matter to another. Analogous phenomena have recently been observed in large language models. Typically, the task…

Machine Learning · Computer Science 2024-05-28 Julian Arnold , Flemming Holtorf , Frank Schäfer , Niels Lörch

We study the problem of change point localisation and inference for sequentially collected fragmented functional data, where each curve is observed only over discrete grids randomly sampled over a short fragment. The sequence of underlying…

Methodology · Statistics 2024-05-10 Gengyu Xue , Haotian Xu , Yi Yu

When analysing time series an important issue is to decide whether the time series is stationary or a random walk. Relaxing these notions, we consider the problem to decide in favor of the I(0)- or I(1)-property. Fixed-sample statistical…

Statistics Theory · Mathematics 2018-05-01 Ansgar Steland

We consider the detection and localization of change points in the distribution of an offline sequence of observations. Based on a nonparametric framework that uses a similarity graph among observations, we propose new test statistics when…

Methodology · Statistics 2021-03-05 Lizhen Nie , Dan L. Nicolae

Among the main goals in multiple change point problems are the estimation of the number and positions of the change points, as well as the regime structure in the clusters induced by those changes. The product partition model (PPM) is a…

Methodology · Statistics 2021-08-11 Ricardo C. Pedroso , Rosangela H. Loschi , Fernando Andrés Quintana

We study the problem of change point localization in dynamic networks models. We assume that we observe a sequence of independent adjacency matrices of the same size, each corresponding to a realization of an unknown inhomogeneous Bernoulli…

Methodology · Statistics 2020-10-22 Daren Wang , Yi Yu , Alessandro Rinaldo

The aim of change-point detection is to identify behavioral shifts within time series data. This article focuses on scenarios where the data is derived from an inhomogeneous Poisson process or a marked Poisson process. We present a…

Methodology · Statistics 2024-11-07 C. Dion-Blanc , D. Hawat , E. Lebarbier , S. Robin

This paper develops a novel method to estimate firm-specific market-entry thresholds in international economics, allowing fixed costs to vary across firms alongside productivity. Our framework models market entry as an interaction between…

General Economics · Economics 2026-01-15 Peter H. Egger , Yulong Wang

We address the problem of policy evaluation in discounted Markov decision processes, and provide instance-dependent guarantees on the $\ell_\infty$-error under a generative model. We establish both asymptotic and non-asymptotic versions of…

Machine Learning · Statistics 2020-03-17 Koulik Khamaru , Ashwin Pananjady , Feng Ruan , Martin J. Wainwright , Michael I. Jordan

As input data distributions evolve, the predictive performance of machine learning models tends to deteriorate. In practice, new input data tend to come without target labels. Then, state-of-the-art techniques model input data distributions…

Machine Learning · Computer Science 2023-09-08 Carlos Mougan , Klaus Broelemann , David Masip , Gjergji Kasneci , Thanassis Thiropanis , Steffen Staab

In this paper, I propose a general procedure for multivariate distribution-free nonparametric testing derived from the concept of ranks that are based upon measure transportation in the context of multiple change point analysis. I will use…

Other Statistics · Statistics 2021-08-30 Amanda Ng

Researchers are often interested in examining between-individual differences in within-individual processes. If the process under investigation is tracked for a long time, its trajectory may show a certain degree of nonlinearity, so that…

Methodology · Statistics 2025-12-02 Jin Liu , Robert A. Perera

The classical problem of quickest change detection is studied with an additional constraint on the cost of observations used in the detection process. The change point is modeled as an unknown constant, and minimax formulations are proposed…

Statistics Theory · Mathematics 2012-11-19 Taposh Banerjee , Venugopal V. Veeravalli

Detecting a change point is a crucial task in statistics that has been recently extended to the quantum realm. A source state generator that emits a series of single photons in a default state suffers an alteration at some point and starts…

Suppose a process yields independent observations whose distributions belong to a family parameterized by \theta\in\Theta. When the process is in control, the observations are i.i.d. with a known parameter value \theta_0. When the process…

Statistics Theory · Mathematics 2007-06-13 Gary Lorden , Moshe Pollak
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