Cover Image

Seeded intervals and noise level estimation in change point detection: A discussion of Fryzlewicz (2020)

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kovács, Solt, Li, Housen, Bühlmann, Peter
Format:	Preprint
Published:	2020
Subjects:	Methodology Computation
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimistic search: Change point estimation for large-scale data via adaptive logarithmic queries
by: Kovács, Solt, et al.
Published: (2020)

Covariance scanning for adaptively optimal change point detection in high-dimensional linear models
by: Cho, Haeran, et al.
Published: (2025)

Assessing the overall and partial causal well-specification of nonlinear additive noise models
by: Schultheiss, Christoph, et al.
Published: (2023)

Causal inference using invariant prediction: identification and confidence intervals
by: Peters, Jonas, et al.
Published: (2015)

Causality-oriented robustness: exploiting general noise interventions
by: Shen, Xinwei, et al.
Published: (2023)

Clustered random forests with correlated data for optimal estimation and inference under potential covariate shift
by: Young, Elliot H., et al.
Published: (2025)

BLAST: Bayesian online change-point detection with structured image data
by: Zheng, Xiaojun, et al.
Published: (2025)

Detection and inference of changes in high-dimensional linear regression with non-sparse structures
by: Cho, Haeran, et al.
Published: (2024)

Multiscale Quantile Regression with Local Error Control
by: Liu, Zhi, et al.
Published: (2024)

Robust covariance estimation and explainable outlier detection for matrix-valued data
by: Mayrhofer, Marcus, et al.
Published: (2024)

Multiple change-point detection for some point processes
by: Dion-Blanc, C., et al.
Published: (2023)

Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
by: Gamella, Juan L., et al.
Published: (2022)

Machine-Learning-Powered Specification Testing in Linear Instrumental Variable Models
by: Scheidegger, Cyrill, et al.
Published: (2025)

Spectral Deconfounding for High-Dimensional Sparse Additive Models
by: Scheidegger, Cyrill, et al.
Published: (2023)

Inference for Heterogeneous Treatment Effects with Efficient Instruments and Machine Learning
by: Scheidegger, Cyrill, et al.
Published: (2025)

Ancestor regression in structural vector autoregressive models
by: Schultheiss, Christoph, et al.
Published: (2024)

Factorized Binary Search: change point detection in the network structure of multivariate high-dimensional time series
by: Ondrus, Martin, et al.
Published: (2021)

Rank estimation for the accelerated failure time model with partially interval-censored data
by: Choi, Taehwa, et al.
Published: (2025)

Extrapolation-Aware Nonparametric Statistical Inference
by: Pfister, Niklas, et al.
Published: (2024)

A Bayesian framework for change-point detection with uncertainty quantification
by: Berlind, Davis, et al.
Published: (2025)

Bayesian variance change point detection with credible sets
by: Cappello, Lorenzo, et al.
Published: (2022)

Bayesian optimal change point detection in high-dimensions
by: Kim, Jaehoon, et al.
Published: (2024)

Model Selection over Partially Ordered Sets
by: Taeb, Armeen, et al.
Published: (2023)

Distributionally Robust Learning for Multi-source Unsupervised Domain Adaptation
by: Wang, Zhenyu, et al.
Published: (2023)

Causality-Inspired Robustness for Nonlinear Models via Representation Learning
by: Šola, Marin, et al.
Published: (2025)

A spectral approach for online covariance change point detection
by: Bao, Zhigang, et al.
Published: (2026)

Robust variable selection for spatial point processes observed with noise
by: Sturm, Dominik, et al.
Published: (2025)

Cubature scheme for spatio-temporal Poisson point processes estimation
by: D'Angelo, Nicoletta, et al.
Published: (2024)

Multilayer random dot product graphs: Estimation and online change point detection
by: Wang, Fan, et al.
Published: (2023)

Change-point detection in regression models for ordered data via the max-EM algorithm
by: Diabaté, Modibo, et al.
Published: (2024)

Online network change point detection with missing values and temporal dependence
by: Xu, Haotian, et al.
Published: (2021)

MOPED: A moving sum method for change point detection in pairwise extremal dependence
by: McGonigle, Euan T., et al.
Published: (2025)

Robustness Against Weak or Invalid Instruments: Exploring Nonlinear Treatment Models with Machine Learning
by: Guo, Zijian, et al.
Published: (2022)

Testing for a general changepoint in psychometric studies: changes detection and sample size planning
by: D'Angelo, Nicoletta
Published: (2024)

Multiple change-point detection on the circle via isolation using permutation testing
by: Loizidou, Sophia, et al.
Published: (2026)

Moving sum procedure for multiple change point detection in large factor models
by: Barigozzi, Matteo, et al.
Published: (2024)

Invariant Probabilistic Prediction
by: Henzi, Alexander, et al.
Published: (2023)

Joint analysis for multivariate longitudinal and event time data with a change point anchored at interval-censored event time
by: Zhan, Yue, et al.
Published: (2026)

Tensor time series change-point detection in cryptocurrency network data
by: Anastasiou, Andreas, et al.
Published: (2025)

Higher-criticism for sparse multi-stream change-point detection
by: Gong, Tingnan, et al.
Published: (2024)