Multiple changepoint detection with partial information on changepoint times
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Publication:2316608
DOI10.1214/19-EJS1568zbMath1422.62286arXiv1511.07238OpenAlexW2962729840MaRDI QIDQ2316608
Yingbo Li, Anuradha Hewaarachchi, Robert B. Lund
Publication date: 6 August 2019
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1511.07238
empirical Bayestime seriessegmentationvector autoregressionsbivariate datastructural breaksbreakpoints
Nonparametric hypothesis testing (62G10) Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Empirical decision procedures; empirical Bayes procedures (62C12)
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On optimal segmentation and parameter tuning for multiple change-point detection and inference, Short communication: Detecting possibly frequent change-points: wild binary segmentation 2 and steepest-drop model selection, Bayesian nonparametric change point detection for multivariate time series with missing observations
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Cites Work
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- A Mathematical Theory of Communication
- Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
- Bayesian detection of abnormal segments in multiple time series
- Wild binary segmentation for multiple change-point detection
- Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
- Estimation of a noisy discrete-time step function: Bayes and empirical Bayes approaches
- An MDL approach to the climate segmentation problem
- Estimating the number of change-points via Schwarz' criterion
- Time series: theory and methods.
- Estimating the dimension of a model
- Estimation and comparison of multiple change-point models
- Model uncertainty
- Multiple change-point detection: a selective overview
- Consistency of minimum description length model selection for piecewise stationary time series models
- Structural breaks in time series
- Detection and Correction of Artificial Shifts in Climate Series
- Break Detection for a Class of Nonlinear Time Series Models
- Model Selection and the Principle of Minimum Description Length
- A Bayesian Analysis for Change Point Problems
- Bayes Factors
- Optimal Detection of Changepoints With a Linear Computational Cost
- On Sampling Strategies in Bayesian Variable Selection Problems With Large Model Spaces
- Group LASSO for Structural Break Time Series
- Bayesian Variable Selection in Structured High-Dimensional Covariate Spaces With Applications in Genomics
- Testing for Change Points in Time Series
- Bayesian Analysis of Isochores
- Heterogeneous Change Point Inference
- Detection of Multiple Structural Breaks in Multivariate Time Series
- Estimation of Multiple-Regime Threshold Autoregressive Models With Structural Breaks
- Detection of Changes in Multivariate Time Series With Application to EEG Data
- Multiple-Change-Point Detection for High Dimensional Time Series via Sparsified Binary Segmentation
- Inference for Multiple Change Points in Time Series via Likelihood Ratio Scan Statistics
- A pairwise likelihood-based approach for changepoint detection in multivariate time series models
- A Modified Bayes Information Criterion with Applications to the Analysis of Comparative Genomic Hybridization Data
- Estimating the Current Mean of a Normal Distribution which is Subjected to Changes in Time
- Multiple-Change-Point Detection for Auto-Regressive Conditional Heteroscedastic Processes
- Structural Break Estimation for Nonstationary Time Series Models
