Cover Image

Nonparametric inference under shape constraints: past, present and future

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Samworth, Richard J.
Format:	Preprint
Published:	2025
Subjects:	Statistics Theory Computation Methodology Machine Learning 62G05
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning the score under shape constraints
by: Lewis, Rebecca M., et al.
Published: (2025)

Nonparametric inference for Poisson-Laguerre tessellations
by: van der Jagt, Thomas, et al.
Published: (2025)

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

Deep learning with missing data
by: Ma, Tianyi, et al.
Published: (2025)

Efficient adjustment for complex covariates: Gaining efficiency with DOPE
by: Christgau, Alexander Mangulad, et al.
Published: (2024)

Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift
by: Wang, Kaizheng
Published: (2023)

Kernel-Based Nonparametric Tests For Shape Constraints
by: Sen, Rohan
Published: (2025)

Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints
by: Auddy, Arnab, et al.
Published: (2024)

Batched Single-Index Global Multi-Armed Bandits with Covariates
by: Arya, Sakshi, et al.
Published: (2025)

Functional Partial Least-Squares: Adaptive Estimation and Inference
by: Babii, Andrii, et al.
Published: (2024)

Nonparametric classification with missing data
by: Sell, Torben, et al.
Published: (2023)

Nonparametric Bayesian volatility learning under microstructure noise
by: Gugushvili, Shota, et al.
Published: (2018)

Kernel-based estimators for functional causal effects
by: Raykov, Yordan P., et al.
Published: (2025)

Nonparametric inference for ratios of densities via uniformly valid and powerful permutation tests
by: Bordino, Alberto, et al.
Published: (2025)

Upgrading survival models with CARE
by: Underwood, William G., et al.
Published: (2025)

Inference with Mondrian Random Forests
by: Cattaneo, Matias D., et al.
Published: (2023)

Efficient and Minimax Optimal In-context Nonparametric Regression with Transformers
by: Ching, Michelle, et al.
Published: (2026)

Nonparametric Inference on Dose-Response Curves Without the Positivity Condition
by: Zhang, Yikun, et al.
Published: (2024)

Asymptotic Analysis and Practical Evaluation of Jump Rate Estimators in Piecewise-Deterministic Markov Processes
by: Azaïs, Romain, et al.
Published: (2025)

Discriminating Tail Behavior Using Halfspace Depths: Population and Empirical Perspectives
by: Singha, Sibsankar, et al.
Published: (2025)

Optimal empirical Bayes estimation for the Poisson model via minimum-distance methods
by: Jana, Soham, et al.
Published: (2022)

Automatic and location-adaptive estimation in functional single-index regression
by: Novo, Silvia, et al.
Published: (2024)

Wasserstein Spatial Depth
by: Bachoc, François, et al.
Published: (2024)

Convolutional neural networks for valid and efficient causal inference
by: Ghasempour, Mohammad, et al.
Published: (2023)

Bump hunting through density curvature features
by: Chacón, José E., et al.
Published: (2022)

Estimation of a Likelihood Ratio Ordered Family of Distributions
by: Mösching, Alexandre, et al.
Published: (2020)

Doubly Robust Inference on Causal Derivative Effects for Continuous Treatments
by: Zhang, Yikun, et al.
Published: (2025)

Location and scatter halfspace median under α-symmetric distributions
by: Bočinec, Filip, et al.
Published: (2025)

Sparse semiparametric regression when predictors are mixture of functional and high-dimensional variables
by: Novo, Silvia, et al.
Published: (2024)

From Global to Local Correlation: Geometric Decomposition of Statistical Inference
by: Gajer, Pawel, et al.
Published: (2025)

High-dimensional variable clustering based on maxima of a weakly dependent random process
by: Boulin, Alexis, et al.
Published: (2023)

Deep Neural Networks for Doubly Robust Estimation with Nonprobability Survey Samples
by: Dai, Yufang, et al.
Published: (2026)

Tweedie-based nonparametric estimation for semicontinuous mixed densities
by: Lyu, Guanjie, et al.
Published: (2026)

Design-Based Inference under Random Potential Outcomes
by: Yang, Yukai
Published: (2025)

Log-concave density estimation in undirected graphical models
by: Kubjas, Kaie, et al.
Published: (2022)

Randomization Tests for Conditional Group Symmetry
by: Chiu, Kenny, et al.
Published: (2024)

Factor Informed Double Deep Learning For Average Treatment Effect Estimation
by: Fan, Jianqing, et al.
Published: (2025)

Optimal In-context Adaptivity and Distributional Robustness of Transformers
by: Ma, Tianyi, et al.
Published: (2025)

M-estimation under Two-Phase Multiwave Sampling with Applications to Prediction-Powered Inference
by: Kluger, Dan M., et al.
Published: (2026)

Spatial Proportional Hazards Model with Differential Regularization
by: Tedesco, Lorenzo, et al.
Published: (2024)