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A pairwise likelihood-based approach for changepoint detection in multivariate time series models
9 references·2 citing·43 second hop
A pairwise likelihood-based approach for changepoint detection in multivariate time series models (2016)A pairwise likelihood-based approach for …Detection of Multiple Structural Breaks in Multivariate Time Series (2014)Detection of Multiple Structu…A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data (2013)A Nonparametric Approach for …Optimal Detection of Changepoints With a Linear Computational Cost (2012)Optimal Detection of Changepo…Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach (2012)Estimating Space and Space-Ti…An MDL approach to the climate segmentation problem (2010)An MDL approach to the climat…Break detection in the covariance structure of multivariate time series models (2009)Break detection in the covari…Break detection in the covariance structure of multivariate time series models (2009)Break detection in the covari…Break Detection for a Class of Nonlinear Time Series Models (2008)Break Detection for a Class o…Multivariate Stochastic Volatility Models: Bayesian Estimation and Model Comparison (2006)Multivariate Stochastic Volat…Change-point methods for multivariate time-series: paired vectorial observations (2020)Change-point methods for mult…Multiple changepoint detection with partial information on changepoint times (2019)Multiple changepoint detectio…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)A robust approach for estimating change-points in the mean of an $\operatorname{AR}(1)$ process (2017)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)TESTING FOR A CHANGE IN CORRELATION AT AN UNKNOWN POINT IN TIME USING AN EXTENDED FUNCTIONAL DELTA METHOD (2011)Extensions of some classical methods in change point analysis (2014)Uniform change point tests in high dimension (2015)Statistics for Spatial Data (1993)Statistics for Spatial Data. (1993)Interpolation of Spatial Data (1999)Estimation and Prediction in Spatial Models With Block Composite Likelihoods (2013)Extending Moran's Index for Measuring Spatiotemporal Clustering of Geographic Events (2016)30 Years of space–time covariance functions (2020)Forecasting, Structural Time Series Models and the Kalman Filter (1990)Multivariate Simultaneous Generalized ARCH (1995)Dynamic Conditional Correlation (2002)Multivariate Stochastic Volatility (2009)The structure of dynamic correlations in multivariate stochastic volatility models (2009)A Survey on Time-Varying Copulas: Specification, Simulations, and Application (2012)Recursive and Sequential Tests of the Unit Root and Trend Break Hypothesis: Theory and International Evidence (1990)State-Space Models with Regime Switching (1999)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)Fossil fuels consumption and carbon dioxide emissions in G7 countries: Empirical evidence from ARDL bounds testing approach (2021)Estimating the number of change-points via Schwarz' criterion (1988)Limit theorems in change-point analysis (1997)Structural Breaks in Financial Time Series (2009)Multiple-Change-Point Detection for Auto-Regressive Conditional Heteroscedastic Processes (2013)Monitoring procedure for parameter change in causal time series (2014)CONTINUOUS INSPECTION SCHEMES (1954)ecp: AnRPackage for Nonparametric Multiple Change Point Analysis of Multivariate Data (2014)A computationally efficient nonparametric approach for changepoint detection (2016)Genre-based L2 writing instruction and writing-specific psychological factors: The dynamics of change (2018)A survey of methods for time series change point detection (2016)changepoint : An R Package for Changepoint Analysis (2014)Wild binary segmentation for multiple change-point detection (2014)Selective review of offline change point detection methods (2019)Inference for single and multiple change‐points in time series (2013)
this work references cited by second hop

References

  • 2012Optimal Detection of Changepoints With a Linear Computational Cost2,578 cited
  • 2013A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data545 cited
  • 2009Break detection in the covariance structure of multivariate time series models313 cited
  • 2009Break detection in the covariance structure of multivariate time series models247 cited
  • 2006Multivariate Stochastic Volatility Models: Bayesian Estimation and Model Comparison181 cited
  • 2012Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach162 cited
  • 2014Detection of Multiple Structural Breaks in Multivariate Time Series107 cited
  • 2008Break Detection for a Class of Nonlinear Time Series Models96 cited
  • 2010An MDL approach to the climate segmentation problem83 cited

Cited by

  • 2020Change-point methods for multivariate time-series: paired vectorial observations15 cited
  • 2019Multiple changepoint detection with partial information on changepoint times12 cited

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