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Robust multiscale estimation of time-average variance for time series segmentation
16 references·1 citing·37 second hop
Robust multiscale estimation of time-average variance for time series segmentation (2022)Robust multiscale estimation of time-aver…Optimal difference-based variance estimators in time series: A general framework (2022)Optimal difference-based vari…Inference of Breakpoints in High-dimensional Time Series (2021)Inference of Breakpoints in H…Data segmentation algorithms: Univariate mean change and beyond (2021)Data segmentation algorithms:…Multiscale change point detection for dependent data (2020)Multiscale change point detec…Selective review of offline change point detection methods (2019)Selective review of offline c…A robust approach for estimating change-points in the mean of an $\operatorname{AR}(1)$ process (2017)A robust approach for estimat…A MOSUM procedure for the estimation of multiple random change points (2017)A MOSUM procedure for the est…Wild binary segmentation for multiple change-point detection (2014)Wild binary segmentation for …Multiscale Change Point Inference (2014)Multiscale Change Point Infer…A multiple filter test for the detection of rate changes in renewal processes with varying variance (2014)A multiple filter test for th…Structural breaks in time series (2012)Structural breaks in time ser…An MDL approach to the climate segmentation problem (2010)An MDL approach to the climat…A note on studentized confidence intervals for the change-point (2009)A note on studentized confide…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…CONTINUOUS INSPECTION SCHEMES (1954)CONTINUOUS INSPECTION SCHEMESMoving Sum Procedure for Change Point Detection under Piecewise Linearity (2024)Moving Sum Procedure for Chan…Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Testing the null hypothesis of stationarity against the alternative of a unit root (1992)Inference for single and multiple change‐points in time series (2013)A computationally efficient nonparametric approach for changepoint detection (2016)On optimal multiple changepoint algorithms for large data (2016)Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance (1994)Testing and Locating Variance Changepoints with Application to Stock Prices (1997)Changepoint Detection in Periodic and Autocorrelated Time Series (2007)Mean shift testing in correlated data (2011)Changepoint detection in daily precipitation data (2012)Optimal Detection of Changepoints With a Linear Computational Cost (2012)changepoint : An R Package for Changepoint Analysis (2014)Changepoint Detection in the Presence of Outliers (2017)High Dimensional Change Point Estimation via Sparse Projection (2017)Inference About the Change-Point in a Sequence of Random Variables (1970)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)Rank Correlation Methods. (1957)Rank Correlation Methods (1973)A Survey on Concept Drift in Process Mining (2021)Sequential (Quickest) Change Detection: Classical Results and New Directions (2021)Time lag effects of COVID-19 policies on transportation systems: A comparative study of New York City and Seattle (2021)Procedures for Reacting to a Change in Distribution (1971)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)mosum: A Package for Moving Sums in Change-Point Analysis (2021)Multiple change point detection under serial dependence: Wild contrast maximisation and gappy Schwarz algorithm (2023)The state of cumulative sum sequential changepoint testing 70 years after Page (2023)
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References

  • 1954CONTINUOUS INSPECTION SCHEMES5,731 cited
  • 2019Selective review of offline change point detection methods1,361 cited
  • 2014Wild binary segmentation for multiple change-point detection721 cited
  • 1988Estimating the number of change-points via Schwarz' criterion628 cited
  • 2012Structural breaks in time series444 cited
  • 2014Multiscale Change Point Inference320 cited
  • 2000Least‐squares Estimation of an Unknown Number of Shifts in a Time Series276 cited
  • 2017A MOSUM procedure for the estimation of multiple random change points144 cited
  • 2010An MDL approach to the climate segmentation problem83 cited
  • 2021Data segmentation algorithms: Univariate mean change and beyond52 cited
  • 2017A robust approach for estimating change-points in the mean of an $\operatorname{AR}(1)$ process50 cited
  • 2020Multiscale change point detection for dependent data41 cited
  • 2014A multiple filter test for the detection of rate changes in renewal processes with varying variance37 cited
  • 2021Inference of Breakpoints in High-dimensional Time Series32 cited
  • 2022Optimal difference-based variance estimators in time series: A general framework24 cited

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  • 2009A note on studentized confidence intervals for the change-point23 cited
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    • 2024Moving Sum Procedure for Change Point Detection under Piecewise Linearity7 cited