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Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise
16 references·4 citing·29 second hop
Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise (2020)Detecting Abrupt Changes in the Presence …Tail-greedy bottom-up data decompositions and fast multiple change-point detection (2018)Tail-greedy bottom-up data de…Detecting Changes in Slope With an L0 Penalty (2018)Detecting Changes in Slope Wi…Changepoint Detection in the Presence of Outliers (2017)Changepoint Detection in the …A MOSUM procedure for the estimation of multiple random change points (2017)A MOSUM procedure for the est…On optimal multiple changepoint algorithms for large data (2016)On optimal multiple changepoi…Computationally Efficient Changepoint Detection for a Range of Penalties (2015)Computationally Efficient Cha…Wild binary segmentation for multiple change-point detection (2014)Wild binary segmentation for …Multiscale Change Point Inference (2014)Multiscale Change Point Infer…Frontiers in Massive Data Analysis (2013)Frontiers in Massive Data Ana…Optimal Detection of Changepoints With a Linear Computational Cost (2012)Optimal Detection of Changepo…A pruned dynamic programming algorithm to recover the best segmentations with $1$ to $K_{max}$ change-points (2010)A pruned dynamic programming …The Structural Break in the Equity Premium (2005)The Structural Break in the E…Journal De La Société Française De Statistique (2005)Journal De La Société Françai…Least‐squares Estimation of an Unknown Number of Shifts in a Time Series (2000)Least‐squares Estimation of a…Estimating the number of change-points via Schwarz' criterion (1988)Estimating the number of chan…Inference about the Change-Point from Cumulative Sum Tests (1971)Inference about the Change-Po…Multiple change point detection under serial dependence: Wild contrast maximisation and gappy Schwarz algorithm (2023)Multiple change point detecti…gfpop: An R Package for Univariate Graph-Constrained Change-Point Detection (2023)gfpop: An R Package for Univa…Bootstrap confidence intervals for multiple change points based on moving sum procedures (2022)Bootstrap confidence interval…Fast Online Changepoint Detection via Functional Pruning CUSUM statistics (2021)Fast Online Changepoint Detec…Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance (1994)changepoint : An R Package for Changepoint Analysis (2014)High Dimensional Change Point Estimation via Sparse Projection (2017)CONTINUOUS INSPECTION SCHEMES (1954)Estimating the Current Mean of a Normal Distribution which is Subjected to Changes in Time (1964)Inference About the Change-Point in a Sequence of Random Variables (1970)The Changepoint Model for Statistical Process Control (2003)The Cusum Test for Parameter Change in Time Series Models (2003)An Overview of Phase I Analysis for Process Improvement and Monitoring (2014)Nonparametric Methods in Change-Point Problems (1993)Detecting multiple breaks in financial market volatility dynamics (2002)Moment and Memory Properties of Linear Conditional Heteroscedasticity Models, and a New Model (2004)Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets (2013)A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the ‘business cycle’ (1981)Limit theorems in change-point analysis (1997)Detection of Changes in Multivariate Time Series With Application to EEG Data (2014)Inference for Multiple Change Points in Time Series via Likelihood Ratio Scan Statistics (2015)Change-point detection in panel data via double CUSUM statistic (2016)Selective review of offline change point detection methods (2019)Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns (2004)Dealing with Structural Breaks (2005)A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data (2013)A heuristic, iterative algorithm for change-point detection in abrupt change models (2017)Univariate mean change point detection: Penalization, CUSUM and optimality (2020)Most Recent Changepoint Detection in Panel Data (2018)Data segmentation algorithms: Univariate mean change and beyond (2021)Real-time Change-Point Detection: A deep neural network-based adaptive approach for detecting changes in multivariate time series data (2022)Statistical Procedures for Forecasting Criminal Behavior (2013)Big data analytics and big data science: a survey (2016)
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References

  • 2012Optimal Detection of Changepoints With a Linear Computational Cost2,578 cited
  • 2014Wild binary segmentation for multiple change-point detection721 cited
  • 1988Estimating the number of change-points via Schwarz' criterion628 cited
  • 1971Inference about the Change-Point from Cumulative Sum Tests460 cited
  • 2014Multiscale Change Point Inference320 cited
  • 2000Least‐squares Estimation of an Unknown Number of Shifts in a Time Series276 cited
  • 2016On optimal multiple changepoint algorithms for large data187 cited
  • 2013Frontiers in Massive Data Analysis163 cited
  • 2017Changepoint Detection in the Presence of Outliers157 cited
  • 2017A MOSUM procedure for the estimation of multiple random change points144 cited
  • 2005Journal De La Société Française De Statistique142 cited
  • 2015Computationally Efficient Changepoint Detection for a Range of Penalties115 cited
  • 2005The Structural Break in the Equity Premium90 cited
  • 2018Detecting Changes in Slope With an L0 Penalty70 cited
  • 2010A pruned dynamic programming algorithm to recover the best segmentations with $1$ to $K_{max}$ change-points66 cited

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2018
Tail-greedy bottom-up data decompositions and fast multiple change-point detection
55 cited

Cited by

  • 2021Fast Online Changepoint Detection via Functional Pruning CUSUM statistics29 cited
  • 2023Multiple change point detection under serial dependence: Wild contrast maximisation and gappy Schwarz algorithm17 cited
  • 2022Bootstrap confidence intervals for multiple change points based on moving sum procedures14 cited
  • 2023gfpop: An R Package for Univariate Graph-Constrained Change-Point Detection13 cited