Cover Image

Distribution-free inference with hierarchical data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lee, Yonghoon, Barber, Rina Foygel, Willett, Rebecca
Format:	Preprint
Published:	2023
Subjects:	Statistics Theory Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Assumption-free stability for ranking problems
by: Liang, Ruiting, et al.
Published: (2025)

Mosaic inference on panel data
by: Spector, Asher, et al.
Published: (2025)

False discovery rate control with compound p-values
by: Barber, Rina Foygel, et al.
Published: (2025)

Bagging Provides Assumption-free Stability
by: Soloff, Jake A., et al.
Published: (2023)

Theoretical Foundations of Conformal Prediction
by: Angelopoulos, Anastasios N., et al.
Published: (2024)

Stability via resampling: statistical problems beyond the real line
by: Soloff, Jake A., et al.
Published: (2024)

Testing conditional independence under isotonicity
by: Hore, Rohan, et al.
Published: (2025)

Leave a Window Out: Modifying the Jackknife for Predictive Inference in Time Series
by: Jiang, Hanyang, et al.
Published: (2026)

Building a stable classifier with the inflated argmax
by: Soloff, Jake A., et al.
Published: (2024)

Distribution-free two-sample testing with blurred total variation distance
by: Hore, Rohan, et al.
Published: (2026)

Integrating Uncertainty Awareness into Conformalized Quantile Regression
by: Rossellini, Raphael, et al.
Published: (2023)

Algorithmic stability implies training-conditional coverage for distribution-free prediction methods
by: Liang, Ruiting, et al.
Published: (2023)

Predictive inference for time series: why is split conformal effective despite temporal dependence?
by: Barber, Rina Foygel, et al.
Published: (2025)

Hoeffding and Bernstein inequalities for weighted sums of exchangeable random variables
by: Barber, Rina Foygel
Published: (2024)

The Limits of Assumption-free Tests for Algorithm Performance
by: Luo, Yuetian, et al.
Published: (2024)

Is Algorithmic Stability Testable? A Unified Framework under Computational Constraints
by: Luo, Yuetian, et al.
Published: (2024)

Unifying Different Theories of Conformal Prediction
by: Barber, Rina Foygel, et al.
Published: (2025)

Pooling information in likelihood-free inference
by: Frazier, David T., et al.
Published: (2022)

Are all models wrong? Fundamental limits in distribution-free empirical model falsification
by: Müller, Manuel M., et al.
Published: (2025)

Two-sample inference for sparse functional data
by: Zhang, Chi, et al.
Published: (2023)

Distribution-uniform anytime-valid sequential inference and the Robbins-Siegmund distributions
by: Waudby-Smith, Ian, et al.
Published: (2023)

Differentially private inference framework of Riemannian manifold data
by: Jiang, Yangdi, et al.
Published: (2026)

Approximating full conformal prediction: distribution free guarantees via the tournament correction
by: Bhattacharyya, Aabesh, et al.
Published: (2026)

Can a calibration metric be both testable and actionable?
by: Rossellini, Raphael, et al.
Published: (2025)

Approximate co-sufficient sampling with regularization
by: Zhu, Wanrong, et al.
Published: (2023)

Conformal prediction with local weights: randomization enables local guarantees
by: Hore, Rohan, et al.
Published: (2023)

Group-Weighted Conformal Prediction
by: Bhattacharyya, Aabesh, et al.
Published: (2024)

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

Turning the information-sharing dial: efficient inference from different data sources
by: Hector, Emily C., et al.
Published: (2022)

Stability and Accuracy Trade-offs in Statistical Estimation
by: Chakraborty, Abhinav, et al.
Published: (2026)

Neymanian inference in randomized experiments
by: Chattopadhyay, Ambarish, et al.
Published: (2024)

Low-order outcomes and clustered designs: combining design and analysis for causal inference under network interference
by: Eichhorn, Matthew, et al.
Published: (2024)

Conformal prediction after data-dependent model selection
by: Liang, Ruiting, et al.
Published: (2024)

Improved bounds and inference on optimal regimes
by: Laurendeau, Julien D., et al.
Published: (2024)

Optimal inference for the mean of random functions
by: Kassi, Omar, et al.
Published: (2025)

A new look at fiducial inference
by: Bissiri, Pier Giovanni, et al.
Published: (2025)

Selective inference is easier with p-values
by: Sood, Anav
Published: (2024)

Uniform inference in linear mixed models
by: Ekvall, Karl Oskar, et al.
Published: (2025)

On inference for modularity statistics in structured networks
by: Mitra, Anirban, et al.
Published: (2024)

Distributionally robust risk evaluation with an isotonic constraint
by: Gui, Yu, et al.
Published: (2024)