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Narrowest-Over-Threshold Detection of Multiple Change Points and Change-Point-Like Features

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/jae.659openalex-snapshot
Computation and analysis of multiple structural change models
inferredcites →https://doi.org/10.1002/joc.3447openalex-snapshot
A Bayesian approach to detecting change points in climatic records
inferredcites →https://doi.org/10.1007/978-1-4612-6333-3openalex-snapshot
A Practical Guide to Splines
inferredcites →https://doi.org/10.1007/978-1-4899-3150-4openalex-snapshot
Local Polynomial Modelling and its Applications
inferredcites →https://doi.org/10.1007/bf02458835openalex-snapshot
Algorithms for the optimal identification of segment neighborhoods
inferredcites →https://doi.org/10.1007/bfb0011093openalex-snapshot
Building your own wavelets at home
inferredcites →https://doi.org/10.1007/s11222-016-9687-5openalex-snapshot
A computationally efficient nonparametric approach for changepoint detection
inferredcites →https://doi.org/10.1007/s11749-019-00659-1openalex-snapshot
Nuisance-parameter-free changepoint detection in non-stationary series
inferredcites →https://doi.org/10.1007/s42952-020-00085-2openalex-snapshot
Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection—rejoinder
inferredcites →https://doi.org/10.1016/0167-7152(88)90118-6openalex-snapshot
Estimating the number of change-points via Schwarz' criterion
inferredcites →https://doi.org/10.1016/j.sigpro.2005.01.012openalex-snapshot
Using penalized contrasts for the change-point problem
inferredcites →https://doi.org/10.1016/s0167-9473(00)00068-2openalex-snapshot
Fitting multiple change-point models to data
inferredcites →https://doi.org/10.1029/2010rg000345openalex-snapshot
GLOBAL SURFACE TEMPERATURE CHANGE
inferredcites →https://doi.org/10.1080/00401706.1997.10485134openalex-snapshot
Smoothing Methods in Statistics
inferredcites →https://doi.org/10.1080/01621459.1974.10482962openalex-snapshot
The Influence Curve and Its Role in Robust Estimation
inferredcites →https://doi.org/10.1080/01621459.2012.737745openalex-snapshot
Optimal Detection of Changepoints With a Linear Computational Cost
inferredcites →https://doi.org/10.1080/01621459.2016.1270214openalex-snapshot
Unsupervised Self-Normalized Change-Point Testing for Time Series
inferredcites →https://doi.org/10.1080/10618600.2018.1512868openalex-snapshot
Detecting Changes in Slope With an L0 Penalty
inferredcites →https://doi.org/10.1080/14649350120068777openalex-snapshot
The Resurrection of Canary Wharf
inferredcites →https://doi.org/10.1086/304243openalex-snapshot
Nonparametric Estimation of Gamma‐Ray Burst Intensities Using Haar Wavelets
inferredcites →https://doi.org/10.1093/biomet/82.2.385openalex-snapshot
Jump and Sharp Cusp Detection by Wavelets
inferredcites →https://doi.org/10.1093/biomet/93.3.687openalex-snapshot
A Haar–Fisz technique for locally stationary volatility estimation
inferredcites →https://doi.org/10.1093/biomet/asv018openalex-snapshot
Jump information criterion for statistical inference in estimating discontinuous curves
inferredcites →https://doi.org/10.1093/biostatistics/kxh008openalex-snapshot
Circular binary segmentation for the analysis of array-based DNA copy number data
inferredcites →https://doi.org/10.1111/1467-9469.t01-1-00058openalex-snapshot
Estimating the Number of Change Points in Exponential Families Distributions
inferredcites →https://doi.org/10.1111/1467-9868.00071openalex-snapshot
Wavelet Threshold Estimators for Data with Correlated Noise
inferredcites →https://doi.org/10.1111/j.1541-0420.2006.00662.xopenalex-snapshot
A Modified Bayes Information Criterion with Applications to the Analysis of Comparative Genomic Hybridization Data
inferredcites →https://doi.org/10.1111/jtsa.12187openalex-snapshot
Testing for Change‐Points in Long‐Range Dependent Time Series by Means of a Self‐Normalized Wilcoxon Test
inferredcites →https://doi.org/10.1111/rssb.12047openalex-snapshot
Multiscale Change Point Inference
inferredcites →https://doi.org/10.1111/rssb.12202openalex-snapshot
Heterogeneous Change Point Inference
inferredcites →https://doi.org/10.1137/070690274openalex-snapshot
$\ell_1$ Trend Filtering
inferredcites →https://doi.org/10.1198/016214505000000745openalex-snapshot
Structural Break Estimation for Nonstationary Time Series Models
inferredcites →https://doi.org/10.1198/jasa.2010.tm10103openalex-snapshot
Testing for Change Points in Time Series
inferredcites →https://doi.org/10.1198/jcgs.2009.07071openalex-snapshot
The Block Criterion for Multiscale Inference About a Density, With Applications to Other Multiscale Problems
inferredcites →https://doi.org/10.1214/009053604000000067openalex-snapshot
Least angle regression
inferredcites →https://doi.org/10.1214/13-aos1189openalex-snapshot
Adaptive piecewise polynomial estimation via trend filtering
inferredcites →https://doi.org/10.1214/14-aos1210openalex-snapshot
Nonparametric maximum likelihood approach to multiple change-point problems
inferredcites →https://doi.org/10.1214/14-aos1245openalex-snapshot
Wild binary segmentation for multiple change-point detection
inferredcites →https://doi.org/10.1214/16-ejs1131openalex-snapshot
FDR-control in multiscale change-point segmentation
inferredcites →https://doi.org/10.1214/17-aos1662openalex-snapshot
Tail-greedy bottom-up data decompositions and fast multiple change-point detection
inferredcites →https://doi.org/10.1214/19-aos1861openalex-snapshot
Segmentation and estimation of change-point models: False positive control and confidence regions
inferredcites →https://doi.org/10.1214/aos/1024691247openalex-snapshot
Minimax estimation of sharp change points
inferredcites →https://doi.org/10.1214/aos/1032298289openalex-snapshot
On the asymptotic performance of median smoothers in image analysis and nonparametric regression
inferredcites →https://doi.org/10.1214/aos/996986504openalex-snapshot
Multiscale Testing of Qualitative Hypotheses
inferredcites →https://doi.org/10.17877/de290r-12194openalex-snapshot
Strucchange: An R Package for Testing for Structural Change in Linear Regression Models
inferredcites →https://doi.org/10.18637/jss.v062.i07openalex-snapshot
ecp: AnRPackage for Nonparametric Multiple Change Point Analysis of Multivariate Data
inferredcites →https://doi.org/10.2307/2998540openalex-snapshot
Estimating and Testing Linear Models with Multiple Structural Changes
inferredcites →https://doi.org/10.32614/cran.package.changepointopenalex-snapshot
changepoint: Methods for Changepoint Detection
inferredcites →https://doi.org/10.4310/sii.2013.v6.n4.a4openalex-snapshot
Adaptive trend estimation in financial time series via multiscale change-point-induced basis recovery
inferredcites →https://doi.org/10.48550/arxiv.1004.0887openalex-snapshot
A pruned dynamic programming algorithm to recover the best segmentations with $1$ to $K_{max}$ change-points
inferredcites →https://doi.org/10.48550/arxiv.1505.04302openalex-snapshot
Change Points via Probabilistically Pruned Objectives
inferredcites →https://doi.org/10.48550/arxiv.1606.06746openalex-snapshot
Approximate Recovery in Changepoint Problems, from $\ell_2$ Estimation Error Rates
inferredcites →https://doi.org/10.48550/arxiv.1701.01672openalex-snapshot
Detecting changes in slope with an $L_0$ penalty
inferredcites →https://doi.org/10.48550/arxiv.1808.01905openalex-snapshot
Nuisance Parameters Free Changepoint Detection in Non-stationary Series
inferredcites →https://doi.org/10.5705/ss.2011.169openalex-snapshot
Detection with the scan and the average likelihood ratio
inferredcites →https://doi.org/10.6084/m9.figshare.1327717openalex-snapshot
Efficient Implementations of the Generalized Lasso Dual Path Algorithm

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4827872openalex-extracted
The Changing Landscape of Cyber Risk: An Empirical Analysis of Frequency, Severity, and Tail Dynamics
inferred← citeshttps://doi.org/10.1002/cjs.11816openalex-snapshot
Multiple change‐point detection for regression curves
inferred← citeshttps://doi.org/10.1002/ece3.8130openalex-snapshot
Flyway‐scale analysis reveals that the timing of migration in wading birds is becoming later
inferred← citeshttps://doi.org/10.1002/sta4.284openalex-snapshot
Determining the number of change‐point via high‐dimensional cross‐validation
inferred← citeshttps://doi.org/10.1002/sta4.291openalex-snapshot
Relating and comparing methods for detecting changes in mean
inferred← citeshttps://doi.org/10.1002/sta4.351openalex-snapshot
Detecting changes in mean in the presence of time‐varying autocovariance
inferred← citeshttps://doi.org/10.1007/978-3-031-08757-8_24openalex-snapshot
Calibration Window Selection Based on Change-Point Detection for Forecasting Electricity Prices
inferred← citeshttps://doi.org/10.1007/978-981-96-8183-9_19openalex-snapshot
Changepoint Detection via Subset Chains
inferred← citeshttps://doi.org/10.1007/s00184-021-00821-6openalex-snapshot
Detecting multiple generalized change-points by isolating single ones
inferred← citeshttps://doi.org/10.1007/s00362-022-01307-xopenalex-snapshot
Epidemic changepoint detection in the presence of nuisance changes
inferred← citeshttps://doi.org/10.1007/s00362-023-01458-5openalex-snapshot
Detecting linear trend changes in data sequences
inferred← citeshttps://doi.org/10.1007/s10463-021-00811-5openalex-snapshot
Two-stage data segmentation permitting multiscale change points, heavy tails and dependence
inferred← citeshttps://doi.org/10.1007/s10463-023-00892-4openalex-snapshot
Data segmentation for time series based on a general moving sum approach
inferred← citeshttps://doi.org/10.1007/s10994-023-06510-xopenalex-snapshot
An encoding approach for stable change point detection
inferred← citeshttps://doi.org/10.1007/s11009-025-10185-3openalex-snapshot
A Partial Review on Testing for Change Points in Autoregressive Time Series Models
inferred← citeshttps://doi.org/10.1007/s11222-023-10261-zopenalex-snapshot
Generalized multiple change-point detection in the structure of multivariate, possibly high-dimensional, data sequences
inferred← citeshttps://doi.org/10.1007/s11222-024-10542-1openalex-snapshot
Improving power by conditioning on less in post-selection inference for changepoints
inferred← citeshttps://doi.org/10.1007/s11222-025-10643-5openalex-snapshot
Data-adaptive structural change-point detection via isolation
inferred← citeshttps://doi.org/10.1007/s11424-023-2342-2openalex-snapshot
Covariate-Assisted Matrix Completion with Multiple Structural Breaks
inferred← citeshttps://doi.org/10.1007/s11425-025-2586-6openalex-snapshot
A robust and efficient tail-adaptive approach for change-point detection in semiparametric models
inferred← citeshttps://doi.org/10.1007/s42519-025-00485-9openalex-snapshot
Volatility Change-Point Detection in $$\beta $$-ARCH(1) Model
inferred← citeshttps://doi.org/10.1007/s42524-026-5394-xopenalex-snapshot
AI for quality management: A review
inferred← citeshttps://doi.org/10.1007/s42952-020-00060-xopenalex-snapshot
Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection
inferred← citeshttps://doi.org/10.1007/s42952-020-00076-3openalex-snapshot
Discussion of ‘Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection’
inferred← citeshttps://doi.org/10.1007/s42952-020-00077-2openalex-snapshot
Seeded intervals and noise level estimation in change point detection: a discussion of Fryzlewicz (2020)
inferred← citeshttps://doi.org/10.1007/s42952-020-00079-0openalex-snapshot
Discussion of ‘Detecting possibly frequent change-points: wild binary segmentation 2 and steepest-drop model selection’
inferred← citeshttps://doi.org/10.1007/s42952-020-00081-6openalex-snapshot
Short communication: Detecting possibly frequent change-points: wild binary segmentation 2 and steepest-drop model selection
inferred← citeshttps://doi.org/10.1007/s42952-020-00085-2openalex-snapshot
Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection—rejoinder
inferred← citeshttps://doi.org/10.1007/s42952-021-00120-wopenalex-snapshot
Ensemble binary segmentation for irregularly spaced data with change-points
inferred← citeshttps://doi.org/10.1016/j.cie.2023.108986openalex-snapshot
A shape-based multiple segmentation algorithm for change-point detection
inferred← citeshttps://doi.org/10.1016/j.cnsns.2025.109535openalex-snapshot
Recursive approach for change point detection in piecewise linear signals
inferred← citeshttps://doi.org/10.1016/j.csda.2022.107648openalex-snapshot
Robust multiscale estimation of time-average variance for time series segmentation
inferred← citeshttps://doi.org/10.1016/j.csda.2023.107705openalex-snapshot
Change-point testing for parallel data sets with FDR control
inferred← citeshttps://doi.org/10.1016/j.csda.2025.108272openalex-snapshot
Robust selection of the number of change-points via FDR control
inferred← citeshttps://doi.org/10.1016/j.econlet.2025.112477openalex-snapshot
Change point analysis in data with heavy tails: A Normal Inverse Gaussian approach
inferred← citeshttps://doi.org/10.1016/j.ecosta.2021.10.008openalex-snapshot
Data segmentation algorithms: Univariate mean change and beyond
inferred← citeshttps://doi.org/10.1016/j.engappai.2026.116204openalex-snapshot
A Statistic-Augmented Neural Network for change point detection and type identification
inferred← citeshttps://doi.org/10.1016/j.jeconom.2020.07.039openalex-snapshot
Time series analysis of COVID-19 infection curve: A change-point perspective
inferred← citeshttps://doi.org/10.1016/j.jmva.2021.104833openalex-snapshot
High dimensional change point inference: Recent developments and extensions
inferred← citeshttps://doi.org/10.1016/j.jocs.2024.102429openalex-snapshot
A Markov random field model for change points detection
inferred← citeshttps://doi.org/10.1016/j.jprocont.2025.103536openalex-snapshot
Operational zone-specific univariate alarm design for incipient faults
inferred← citeshttps://doi.org/10.1016/j.neucom.2026.134647openalex-snapshot
Non-stationarity in financial time series: A taxonomy-based survey of drift detection, adaptation, and evaluation
inferred← citeshttps://doi.org/10.1016/j.spl.2024.110132openalex-snapshot
A novel dual-criterion framework for change point detection
inferred← citeshttps://doi.org/10.1038/s41598-025-96794-xopenalex-snapshot
An automatic sustained attention prediction (ASAP) method for infants and toddlers using wearable device signals
inferred← citeshttps://doi.org/10.1080/00401706.2024.2308202openalex-snapshot
Moving Sum Procedure for Change Point Detection under Piecewise Linearity
inferred← citeshttps://doi.org/10.1080/00949655.2022.2083127openalex-snapshot
On optimal segmentation and parameter tuning for multiple change-point detection and inference
inferred← citeshttps://doi.org/10.1080/01621459.2017.1385466openalex-snapshot
Changepoint Detection in the Presence of Outliers
inferred← citeshttps://doi.org/10.1080/01621459.2020.1859380openalex-snapshot
Multiscale Quantile Segmentation
inferred← citeshttps://doi.org/10.1080/01621459.2021.1999820openalex-snapshot
Data-driven selection of the number of change-points via error rate control
inferred← citeshttps://doi.org/10.1080/01621459.2023.2211733openalex-snapshot
Narrowest Significance Pursuit: Inference for Multiple Change-Points in Linear Models
inferred← citeshttps://doi.org/10.1080/02331888.2021.1977812openalex-snapshot
Robust scale estimation under shifts in the mean
inferred← citeshttps://doi.org/10.1080/02664763.2025.2461186openalex-snapshot
Objective Bayesian trend filtering via adaptive piecewise polynomial regression
inferred← citeshttps://doi.org/10.1080/03610918.2023.2245988openalex-snapshot
Detecting weak changes in the mean of a class of nonlinear heteroscedastic models
inferred← citeshttps://doi.org/10.1080/07350015.2024.2316103openalex-snapshot
Robust Narrowest Significance Pursuit: Inference for Multiple Change-Points in the Median
inferred← citeshttps://doi.org/10.1080/10447318.2024.2440641openalex-snapshot
Evolution of Human–Robot Personality Similarity: A Historical Analysis from 1960 to 2019
inferred← citeshttps://doi.org/10.1080/10618600.2018.1512868openalex-snapshot
Detecting Changes in Slope With an L0 Penalty
inferred← citeshttps://doi.org/10.1080/10618600.2019.1647216openalex-snapshot
Parallelization of a Common Changepoint Detection Method
inferred← citeshttps://doi.org/10.1080/10618600.2023.2262000openalex-snapshot
Smoothing Splines for Discontinuous Signals
inferred← citeshttps://doi.org/10.1080/10618600.2024.2402895openalex-snapshot
Ms.FPOP: A Fast Exact Segmentation Algorithm with a Multiscale Penalty
inferred← citeshttps://doi.org/10.1080/10618600.2026.2686430openalex-snapshot
OPTICS: Order-Preserved Test-Inverse Confidence Set for Number of Change-Points
inferred← citeshttps://doi.org/10.1093/bioinformatics/btad688openalex-snapshot
Nunchaku: optimally partitioning data into piece-wise contiguous segments
inferred← citeshttps://doi.org/10.1093/biomet/asaa049openalex-snapshot
Jump or kink: on super-efficiency in segmented linear regression breakpoint estimation
inferred← citeshttps://doi.org/10.1093/biomet/asac052openalex-snapshot
Seeded binary segmentation: a general methodology for fast and optimal changepoint detection
inferred← citeshttps://doi.org/10.1093/imaiai/iaaf002openalex-snapshot
Degrees-of-freedom penalized piecewise regression
inferred← citeshttps://doi.org/10.1093/jamiaopen/ooac090openalex-snapshot
Automated selection of changepoints using empirical P-values and trimming
inferred← citeshttps://doi.org/10.1093/jrsssb/qkae004openalex-snapshot
Automatic change-point detection in time series via deep learning
inferred← citeshttps://doi.org/10.1093/jrsssb/qkaf029openalex-snapshot
Detection and inference of changes in high-dimensional linear regression with nonsparse structures
inferred← citeshttps://doi.org/10.1093/jrsssb/qkag037openalex-snapshot
ART: distribution-free and model-agnostic changepoint detection with finite-sample guarantees
inferred← citeshttps://doi.org/10.1093/jrsssb/qkag072openalex-snapshot
Inference for structural changes in nonstationary functional time series with partial measurement error
inferred← citeshttps://doi.org/10.1109/ciss.2019.8693028openalex-snapshot
Empirical Bounds on the Rate of Secret Bits Extracted from Received Signal Strength
inferred← citeshttps://doi.org/10.1109/icesc48915.2020.9155958openalex-snapshot
Big Data Cleaning Algorithm based on Repetitive Change Detection and GANs
inferred← citeshttps://doi.org/10.1109/jstsp.2022.3140703openalex-snapshot
Hybrid Modeling of Regional COVID-19 Transmission Dynamics in the U.S.
inferred← citeshttps://doi.org/10.1109/tit.2022.3150253openalex-snapshot
On a Phase Transition in General Order Spline Regression
inferred← citeshttps://doi.org/10.1109/tit.2024.3423325openalex-snapshot
Robust Estimation of High-Dimensional Linear Regression With Changepoints
inferred← citeshttps://doi.org/10.1109/tiv.2024.3443755openalex-snapshot
ReSeleCT: A New Approach for Continual Learning With Application to Vehicle State Estimation
inferred← citeshttps://doi.org/10.1109/tpami.2025.3548012openalex-snapshot
Bayesian Variance Change Point Detection With Credible Sets
inferred← citeshttps://doi.org/10.1109/tsm.2021.3135434openalex-snapshot
ℓ₁ Trend Filtering-Based Change Point Detection for Pumping Line Balance of Deposition Equipment
inferred← citeshttps://doi.org/10.1111/jtsa.12809openalex-snapshot
Gradual Changes in Functional Time Series
inferred← citeshttps://doi.org/10.1111/rssb.12447openalex-snapshot
High-Dimensional, Multiscale Online Changepoint Detection
inferred← citeshttps://doi.org/10.1111/rssb.12453openalex-snapshot
Modelling the COVID-19 Infection Trajectory: A Piecewise Linear Quantile Trend Model
inferred← citeshttps://doi.org/10.1111/rssb.12501openalex-snapshot
Testing for a Change in Mean after Changepoint Detection
inferred← citeshttps://doi.org/10.1111/rssb.12552openalex-snapshot
Segmenting Time Series via Self-Normalisation
inferred← citeshttps://doi.org/10.1111/sjos.12465openalex-snapshot
Multiscale change point detection for dependent data
inferred← citeshttps://doi.org/10.1145/3340804openalex-snapshot
Bayesian Model Selection Approach to Multiple Change-Points Detection with Non-Local Prior Distributions
inferred← citeshttps://doi.org/10.1145/3624354.3630587openalex-snapshot
Change Point Detection in WLANs with Random AP Forests
inferred← citeshttps://doi.org/10.1146/annurev-statistics-041124-044143openalex-snapshot
Change-Point Detection and Its Modern Applications
inferred← citeshttps://doi.org/10.1214/17-aos1662openalex-snapshot
Tail-greedy bottom-up data decompositions and fast multiple change-point detection
inferred← citeshttps://doi.org/10.1214/19-aos1861openalex-snapshot
Segmentation and estimation of change-point models: False positive control and confidence regions
inferred← citeshttps://doi.org/10.1214/20-aos1953openalex-snapshot
Optimal change point detection and localization in sparse dynamic networks
inferred← citeshttps://doi.org/10.1214/20-ejs1710openalex-snapshot
Univariate mean change point detection: Penalization, CUSUM and optimality
inferred← citeshttps://doi.org/10.1214/21-aos2098openalex-snapshot
Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators
inferred← citeshttps://doi.org/10.1214/21-ejs1809openalex-snapshot
Optimal nonparametric change point analysis
inferred← citeshttps://doi.org/10.1214/21-ejs1871openalex-snapshot
A distribution free test for changes in the trend function of locally stationary processes
inferred← citeshttps://doi.org/10.1214/21-ejs1963openalex-snapshot
Localising change points in piecewise polynomials of general degrees
inferred← citeshttps://doi.org/10.1214/22-ejs2048openalex-snapshot
Consistency of a range of penalised cost approaches for detecting multiple changepoints
inferred← citeshttps://doi.org/10.1214/22-ejs2101openalex-snapshot
Multiscale change point detection via gradual bandwidth adjustment in moving sum processes
inferred← citeshttps://doi.org/10.1214/23-aos2297openalex-snapshot
Optimal change-point detection and localization
inferred← citeshttps://doi.org/10.1214/23-ejs2116openalex-snapshot
Estimation of high-dimensional change-points under a group sparsity structure
inferred← citeshttps://doi.org/10.1214/23-ejs2126openalex-snapshot
Optimal multiple change-point detection for high-dimensional data
inferred← citeshttps://doi.org/10.1214/24-aoas1926openalex-snapshot
Multiple change point detection in functional data with applications to biomechanical fatigue data
inferred← citeshttps://doi.org/10.1214/24-aos2451openalex-snapshot
Change-point analysis with irregular signals
inferred← citeshttps://doi.org/10.1214/24-ejs2294openalex-snapshot
Efficient sparsity adaptive changepoint estimation
inferred← citeshttps://doi.org/10.1214/25-ejs2345openalex-snapshot
Fast and optimal inference for change points in piecewise polynomials via differencing
inferred← citeshttps://doi.org/10.1214/26-ejs2485openalex-snapshot
Multiscale detection of practically significant changes in a gradually varying time series
inferred← citeshttps://doi.org/10.1214/26-ejs2523openalex-snapshot
Random interval distillation for detection of change-points in Markov chain Bernoulli networks
inferred← citeshttps://doi.org/10.1287/ijds.2024.0030openalex-snapshot
Detecting Multiple Changepoints by Exploiting Their Spatiotemporal Correlations: A Bayesian Hierarchical Approach
inferred← citeshttps://doi.org/10.1287/ijoc.2021.0313openalex-snapshot
ℓ0 Trend Filtering
inferred← citeshttps://doi.org/10.1371/journal.pone.0256128openalex-snapshot
Structural change detection in ordinal time series
inferred← citeshttps://doi.org/10.1371/journal.pone.0262244openalex-snapshot
Simple epidemic models with segmentation can be better than complex ones
inferred← citeshttps://doi.org/10.1515/ijb-2018-0052openalex-snapshot
Bayesian Detection of Piecewise Linear Trends in Replicated Time-Series with Application to Growth Data Modelling
inferred← citeshttps://doi.org/10.1609/aaai.v38i10.29008openalex-snapshot
Uncertainty Quantification for Data-Driven Change-Point Learning via Cross-Validation
inferred← citeshttps://doi.org/10.17635/lancaster/thesis/1144openalex-snapshot
Understanding declines in the population size of migratory birds
inferred← citeshttps://doi.org/10.17863/cam.62917openalex-snapshot
High-Dimensional, Multiscale Online Changepoint Detection
inferred← citeshttps://doi.org/10.18637/jss.v097.i08openalex-snapshot
mosum: A Package for Moving Sums in Change-Point Analysis
inferred← citeshttps://doi.org/10.18637/jss.v106.i06openalex-snapshot
gfpop: An R Package for Univariate Graph-Constrained Change-Point Detection
inferred← citeshttps://doi.org/10.18637/jss.v109.i07openalex-snapshot
cpop: Detecting Changes in Piecewise-Linear Signals
inferred← citeshttps://doi.org/10.26686/wgtn.19107623openalex-snapshot
Improving automatic processing of wildlife sound recordings
inferred← citeshttps://doi.org/10.3150/20-bej1249openalex-snapshot
Optimal covariance change point detection in high dimension
inferred← citeshttps://doi.org/10.32614/cran.package.notopenalex-snapshot
not: Narrowest-Over-Threshold Change-Point Detection
inferred← citeshttps://doi.org/10.3390/axioms14060402openalex-snapshot
Change-Point Estimation and Detection for Mixture of Linear Regression Models
inferred← citeshttps://doi.org/10.3390/e28090961openalex-snapshot
A Fast Multiple Change-Point Detection Method via Generalized Nearly Isotonic Optimization
inferred← citeshttps://doi.org/10.3934/math.20251311openalex-snapshot
Window-sliding based NSP algorithm for multiple change-points estimation
inferred← citeshttps://doi.org/10.3934/math.2025216openalex-snapshot
Bayesian multiple changing-points detection
inferred← citeshttps://doi.org/10.48550/arxiv.1701.01672openalex-snapshot
Detecting changes in slope with an $L_0$ penalty
inferred← citeshttps://doi.org/10.48550/arxiv.2004.08159openalex-snapshot
Detection and Estimation of Local Signals
inferred← citeshttps://doi.org/10.48550/arxiv.2005.11132openalex-snapshot
A distribution free test for changes in the trend function of locally stationary processes
inferred← citeshttps://doi.org/10.48550/arxiv.2006.10845openalex-snapshot
Short Communication: Detecting Possibly Frequent Change-points: Wild Binary Segmentation 2
inferred← citeshttps://doi.org/10.48550/arxiv.2006.14273openalex-snapshot
Discussion of 'Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection'
inferred← citeshttps://doi.org/10.48550/arxiv.2007.04553openalex-snapshot
Time Series Analysis of COVID-19 Infection Curve: A Change-Point Perspective
inferred← citeshttps://doi.org/10.48550/arxiv.2011.01857openalex-snapshot
A review on minimax rates in change point detection and localisation
inferred← citeshttps://doi.org/10.48550/arxiv.2011.09437openalex-snapshot
Trend and Variance Adaptive Bayesian Changepoint Analysis & Local Outlier Scoring
inferred← citeshttps://doi.org/10.48550/arxiv.2012.11573openalex-snapshot
Change-in-Slope Optimal Partitioning Algorithm in a Finite-Size Parameter Space
inferred← citeshttps://doi.org/10.48550/arxiv.2101.08597openalex-snapshot
On detecting weak changes in the mean of CHARN models
inferred← citeshttps://doi.org/10.48550/arxiv.2104.12022openalex-snapshot
Valid Post-Detection Inference for Change Points Identified Using Trend Filtering
inferred← citeshttps://doi.org/10.52280/j7cty911openalex-snapshot
An Online Detection Method for Identifying True Change Points
inferred← citeshttps://doi.org/10.52933/jdssv.v2i7.50openalex-snapshot
Multiple Changepoint Analysis of COVID-19 Infection Progression and Related Deaths in the Small Island State of Malta
inferred← citeshttps://doi.org/10.5705/ss.202020.0464openalex-snapshot
Detecting Multiple Change Points: The PULSE Criterion
inferred← citeshttps://doi.org/10.5705/ss.202021.0181openalex-snapshot
Collective Anomaly Detection in High-Dimensional Var Models
inferred← citeshttps://doi.org/10.5705/ss.202023.0017openalex-snapshot
Multiscale Autoregression on Adaptively Detected Timescales
inferred← citeshttps://doi.org/10.6084/m9.figshare.13342188openalex-snapshot
Multiscale Quantile Segmentation
inferred← citeshttps://doi.org/10.70675/4790f7c4z44c5z455fz971czb5726fa6cc8eopenalex-snapshot
Contributions to ranking problems and high-dimensional change-point detection
inferred← citeshttps://doi.org/10.70675/643b4580zcc6dz4a07zb295z99791353a52copenalex-snapshot
Geometric functional pruning for change point detection in low-dimensional exponential family models.
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.