Cover Image

Cross-validation for change-point regression: pitfalls and solutions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pein, Florian, Shah, Rajen D.
Format:	Preprint
Published:	2021
Subjects:	Methodology Statistics Theory Computation Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Outrigger local polynomial regression
by: Young, Elliot H., et al.
Published: (2026)

Change-point regression with a smooth additive disturbance
by: Pein, Florian, et al.
Published: (2021)

Cross-validation: what does it estimate and how well does it do it?
by: Bates, Stephen, et al.
Published: (2021)

Detection of collective and point anomalies at the presence of trend and seasonality
by: Zhang, Yiyin, et al.
Published: (2025)

Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders
by: Wang, Yuhao, et al.
Published: (2020)

Average partial effect estimation using double machine learning
by: Klyne, Harvey, et al.
Published: (2023)

The Projected Covariance Measure for assumption-lean variable significance testing
by: Lundborg, Anton Rask, et al.
Published: (2022)

Latent confounding in high-dimensional nonlinear models
by: Wang, Yuhao, et al.
Published: (2025)

Monte Carlo inference for semiparametric Bayesian regression
by: Kowal, Daniel R., et al.
Published: (2023)

Sandwich Boosting for Accurate Estimation in Partially Linear Models for Grouped Data
by: Young, Elliot H., et al.
Published: (2023)

Rank-transformed subsampling: inference for multiple data splitting and exchangeable p-values
by: Guo, F. Richard, et al.
Published: (2023)

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

Augmented transfer regression learning for completely missing covariates
by: Zhao, Huali, et al.
Published: (2026)

Adversarial learning for nonparametric regression: Minimax rate and adaptive estimation
by: Peng, Jingfu, et al.
Published: (2025)

High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior
by: Mai, The Tien
Published: (2025)

Anytime-valid off-policy inference for contextual bandits
by: Waudby-Smith, Ian, et al.
Published: (2022)

Corrected generalized cross-validation for finite ensembles of penalized estimators
by: Bellec, Pierre C., et al.
Published: (2023)

Dimension-free bounds in high-dimensional linear regression via error-in-operator approach
by: Noskov, Fedor, et al.
Published: (2025)

Anytime-valid t-tests and confidence sequences for Gaussian means with unknown variance
by: Wang, Hongjian, et al.
Published: (2023)

Estimating Graph Dimension with Cross-validated Eigenvalues
by: Chen, Fan, et al.
Published: (2021)

Handling bounded response in high dimensions: a Horseshoe prior Bayesian Beta regression approach
by: Mai, The Tien
Published: (2025)

A new approach to locally adaptive polynomial regression
by: Chatterjee, Sabyasachi, et al.
Published: (2024)

Bootstrapping the Cross-Validation Estimate
by: Cai, Bryan, et al.
Published: (2023)

Theoretical guarantees for change localization using conformal p-values
by: Bhattacharyya, Swapnaneel, et al.
Published: (2025)

High-dimensional analysis of ridge regression for non-identically distributed data with a variance profile
by: Bigot, Jérémie, et al.
Published: (2024)

High-dimensional ridge regression with random features for non-identically distributed data with a variance profile
by: Dabo, Issa-Mbenard, et al.
Published: (2025)

Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices
by: de Surrel, Thibault, et al.
Published: (2025)

Double Cross-fit Doubly Robust Estimators: Beyond Series Regression
by: McClean, Alec, et al.
Published: (2024)

Kernel Thinning
by: Dwivedi, Raaz, et al.
Published: (2021)

A partial likelihood approach to tree-based density modeling and its application in Bayesian inference
by: Ma, Li, et al.
Published: (2024)

The Proximal Robbins-Monro Method
by: Toulis, Panos, et al.
Published: (2015)

Beyond Basic A/B testing: Improving Statistical Efficiency for Business Growth
by: Wei, Changshuai, et al.
Published: (2025)

Block Empirical Likelihood Inference for Longitudinal Generalized Partially Linear Single-Index Models
by: Zhang, Tianni, et al.
Published: (2026)

Inference in Randomized Least Squares and PCA via Normality of Quadratic Forms
by: Wang, Leda, et al.
Published: (2024)

A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques
by: Li, Xuetong, et al.
Published: (2024)

High-Dimensional Statistics: Reflections on Progress and Open Problems
by: Maleki, Arian, et al.
Published: (2026)

Intrinsic effective sample size for manifold-valued Markov chain Monte Carlo via kernel discrepancy
by: You, Kisung
Published: (2026)

Uncertainty quantification for iterative algorithms in linear models with application to early stopping
by: Bellec, Pierre C., et al.
Published: (2024)

Conjugate gradient methods for high-dimensional GLMMs
by: Pandolfi, Andrea, et al.
Published: (2024)

A note on the unique properties of the Kullback--Leibler divergence for sampling via gradient flows
by: Crucinio, Francesca Romana
Published: (2025)