One-step estimation of differentiable Hilbert-valued parameters
From MaRDI portal
Publication:6621535
DOI10.1214/24-aos2403MaRDI QIDQ6621535
Publication date: 18 October 2024
Published in: The Annals of Statistics (Search for Journal in Brave)
Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Nonparametric tolerance and confidence regions (62G15)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Greedy function approximation: A gradient boosting machine.
- Higher order tangent spaces and influence functions
- On Sobolev orthogonal polynomials
- On differentiable functionals
- Sobolev spaces associated to the harmonic oscillator
- Bootstrapping general empirical measures
- Contributions to a general asymptotic statistical theory. With the assistance of W. Wefelmeyer
- On asymptotically efficient estimation in semiparametric models
- Consistent estimation of the influence function of locally asymptotically linear estimators
- Estimation in semiparametric models. Some recent developments
- Bootstrap methods: another look at the jackknife
- Extremal probabilities for Gaussian quadratic forms
- Minimax estimation of a functional on a structured high-dimensional model
- Unified methods for censored longitudinal data and causality
- Weak convergence and empirical processes. With applications to statistics
- Semiparametric theory and missing data.
- An introduction to infinite-dimensional analysis
- An Omnibus Non-Parametric Test of Equality in Distribution for Unknown Functions
- Oracle inequalities for multi-fold cross validation
- What is a Sobolev space for the Laguerre function systems?
- Higher order influence functions and minimax estimation of nonlinear functionals
- Estimation of Distribution Density Belonging to a Class of Entire Functions
- A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect
- Quasi-oracle estimation of heterogeneous treatment effects
- Demystifying Statistical Learning Based on Efficient Influence Functions
- Debiased machine learning of global and local parameters using regularized Riesz representers
- Double/debiased machine learning for treatment and structural parameters
- Non-parametric Methods for Doubly Robust Estimation of Continuous Treatment Effects
- Estimation of Probability Density by an Orthogonal Series
- Applications of reproducing kernel Hilbert spaces–bandlimited signal models
- On the Asymptotic Distribution of Differentiable Statistical Functions
- A simple and general debiased machine learning theorem with finite-sample guarantees
- Towards optimal doubly robust estimation of heterogeneous causal effects
- A General Framework for Inference on Algorithm-Agnostic Variable Importance
- Orthogonal statistical learning
- Semiparametric counterfactual density estimation
- Minimax rates for heterogeneous causal effect estimation
- Super-learning of an optimal dynamic treatment rule
- Statistical inference for variable importance
- Targeted maximum likelihood learning
This page was built for publication: One-step estimation of differentiable Hilbert-valued parameters