Results 51 to 60 of about 2,607,610 (251)

gfpop: An R Package for Univariate Graph-Constrained Change-Point Detection

Journal of Statistical Software, 2023
In a world with data that change rapidly and abruptly, it is important to detect those changes accurately. In this paper we describe an R package implementing a generalized version of an algorithm recently proposed by Hocking, Rigaill, Fearnhead, and ...
Vincent Runge, Toby Dylan Hocking, Gaetano Romano, Fatemeh Afghah, Paul Fearnhead, Guillem Rigaill   +5 more
doaj   +1 more source

Ratio tests for change point detection

, 2008
We propose new tests to detect a change in the mean of a time series. Like many existing tests, the new ones are based on the CUSUM process. Existing CUSUM tests require an estimator of a scale parameter to make them asymptotically distribution free ...
Horváth, Lajos, Horváth, Zsuzsanna, Hušková, Marie   +2 more
core   +1 more source

Retrospective Change-Points Detection for Multidimensional Time Series of Arbitrary Nature: Model-Free Technology Based on the ϵ-Complexity Theory

Entropy, 2021
We consider a retrospective change-point detection problem for multidimensional time series of arbitrary nature (in particular, panel data). Change-points are the moments at which the changes in generating mechanism occur.
Alexandra Piryatinska, Boris Darkhovsky
doaj   +1 more source

Dynamic change-point detection using similarity networks

, 2016
From a sequence of similarity networks, with edges representing certain similarity measures between nodes, we are interested in detecting a change-point which changes the statistical property of the networks. After the change, a subset of anomalous nodes
Cao, Shanshan, Xie, Yao
core   +1 more source

Detecting change-points in extremes [PDF]

Statistics and Its Interface, 2015
Even though most work on change-point estimation focuses on changes in the mean, changes in the variance or in the tail distribution can lead to more extreme events. In this paper, we develop a new method of detecting and estimating the change-points in the tail of multiple time series data.
Dupuis, D. J., Sun, Ying, Wang, Huixia Judy   +2 more
openaire   +2 more sources

Application and Optimization of Algorithms for Pressure Wave Evaluation Based on Measurement Data

Applied Sciences, 2022
Leakages can occur in a district heating network, resulting in high economical damage. The propagating pressure wave resulting from large, spontaneous leakages reaches sensors at different locations in the network. This leads to pressure drops registered
Kai Vahldiek, Yao Yao, Bernd Rüger, Frank Klawonn   +3 more
doaj   +1 more source

The HIT Network for Children and Adolescents With CNS Tumors Facilitates Improvements of Diagnostic Assessments, Multimodal Treatments, Individual Counseling, and Research in Germany, Austria, and Switzerland

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background The HIT network was established in 2000 to create a population‐based structure aiming to improve survival rates and reduce late effects for children with central nervous system (CNS) tumors by conducting comprehensive clinical trials.
Stefan Rutkowski, Michael C. Frühwald, Gudrun Fleischhack, Stephan Tippelt, Pablo Hernáiz‐Driever, Olaf Witt, Astrid Gnekow, Christof Kramm, Matthias Eyrich, Johannes E. A. Wolf, Hermann Müller, Carsten Friedrich, Uwe R. Kordes, Denise Obrecht‐Sturm, Petra Ketteler, Barbara von Zezschwitz, Pascal Johann, Dominik Sturm, Karoline Nemes, Stefan Schönberger, Till Milde, Brigitte Bison, Monika Warmuth‐Metz, Torsten Pietsch, Ulrich Schüller, Arend Koch, David Capper, Martin Hasselblatt, Christian Thomas, Christian Hagel, Stefan M. Pfister, Felix Sahm, David T. W. Jones, Martin U. Schuhmann, Jürgen Krauss, Pedram Emami, Ahmed El Damaty, Rolf D. Kortmann, Rudolf Schwarz, Jürgen Debus, Mechthild Krause, Fabian Pohl, Holger Ottensmeier, Lisa Bußenius, Katja Baust, Andreas Faldum, Cecile Ronckers, Desiree Grabow, Martin Benesch, Thomas Perwein, Karin Dieckmann, Irene Slavc, Johannes Gojo, Nicolas U. Gerber, André O. von Bueren, Katrin Scheinemann, Gabriele Calaminus, Beate Timmermann, Ulrich‐Wilhelm Thomale, Martin Mynarek   +59 more
wiley   +1 more source

Pruning and Nonparametric Multiple Change Point Detection

, 2017
Change point analysis is a statistical tool to identify homogeneity within time series data. We propose a pruning approach for approximate nonparametric estimation of multiple change points.
James, Nicholas, Matteson, David, Zhang, Wenyu   +2 more
core   +1 more source

Dimension-agnostic change point detection

Journal of Econometrics
Change point testing for high-dimensional data has attracted a lot of attention in statistics and machine learning owing to the emergence of high-dimensional data with structural breaks from many fields. In practice, when the dimension is less than the sample size but is not small, it is often unclear whether a method that is tailored to high ...
Hanjia Gao, Runmin Wang, Xiaofeng Shao
openaire   +2 more sources

Dynamic Interpretable Change Point Detection

, 2022
Identifying change points (CPs) in a time series is crucial to guide better decision making across various fields like finance and healthcare and facilitating timely responses to potential risks or opportunities. Existing Change Point Detection (CPD) methods have a limitation in tracking changes in the joint distribution of multidimensional features ...
Garg, Kopal, Yu, Jennifer, Behrouzi, Tina, Tonekaboni, Sana, Goldenberg, Anna   +4 more
openaire   +2 more sources