Annals of Statistics

Papers
(The TQCC of Annals of Statistics is 7. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-02-01 to 2025-02-01.)
ArticleCitations
Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences108
On singular values of data matrices with general independent columns93
Optimal estimation and computational limit of low-rank Gaussian mixtures61
Ridge regression revisited: Debiasing, thresholding and bootstrap52
Change-point analysis with irregular signals51
Online inference with multi-modal likelihood functions50
Statistical inference for rough volatility: Minimax theory46
On the approximation accuracy of Gaussian variational inference46
One-step estimation of differentiable Hilbert-valued parameters45
Conformal prediction beyond exchangeability36
Online change-point detection for matrix-valued time series with latent two-way factor structure36
Generalization error bounds of dynamic treatment regimes in penalized regression-based learning33
Foundations of structural causal models with cycles and latent variables32
Maximum likelihood for high-noise group orbit estimation and single-particle cryo-EM31
High-dimensional nonparametric density estimation via symmetry and shape constraints28
Principal components in linear mixed models with general bulk27
Inference in Ising models on dense regular graphs27
A cross-validation framework for signal denoising with applications to trend filtering, dyadic CART and beyond27
Extreme value inference for heterogeneous power law data27
Off-policy evaluation in partially observed Markov decision processes under sequential ignorability27
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes27
Dispersal density estimation across scales25
False discovery rate control with unknown null distribution: Is it possible to mimic the oracle?24
On the disjoint and sliding block maxima method for piecewise stationary time series23
Carving model-free inference23
Parametric copula adjusted for non- and semiparametric regression23
Concentration of kernel matrices with application to kernel spectral clustering21
Orthogonal statistical learning21
Metric statistics: Exploration and inference for random objects with distance profiles21
Robust k-means clustering for distributions with two moments21
A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids20
Adaptive estimation in multivariate response regression with hidden variables20
The adaptive Wynn algorithm in generalized linear models with univariate response20
Estimation and inference for minimizer and minimum of convex functions: Optimality, adaptivity and uncertainty principles19
Optimal disclosure risk assessment19
Large-scale inference with block structure19
Optimization hierarchy for fair statistical decision problems18
Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators17
Half-trek criterion for identifiability of latent variable models17
Sharp minimax distribution estimation for current status censoring with or without missing17
Choosing between persistent and stationary volatility17
Boosted nonparametric hazards with time-dependent covariates16
ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM16
On universally consistent and fully distribution-free rank tests of vector independence16
Convergence rates of oblique regression trees for flexible function libraries16
Distribution and quantile functions, ranks and signs in dimension d: A measure transportation approach16
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression16
Parameter estimation in nonlinear multivariate stochastic differential equations based on splitting schemes16
The Stein effect for Fréchet means15
Tensor clustering with planted structures: Statistical optimality and computational limits15
Scalable estimation and inference for censored quantile regression process15
Variable selection consistency of Gaussian process regression15
Measuring dependence in the Wasserstein distance for Bayesian nonparametric models14
Deep learning for the partially linear Cox model14
On high-dimensional Poisson models with measurement error: Hypothesis testing for nonlinear nonconvex optimization14
Stein’s method of normal approximation: Some recollections and reflections14
On an extension of the promotion time cure model14
Complex sampling designs: Uniform limit theorems and applications14
Nonparametric Bayesian inference for reversible multidimensional diffusions14
Adaptive robust estimation in sparse vector model14
Universal rank inference via residual subsampling with application to large networks14
Wasserstein $F$-tests and confidence bands for the Fréchet regression of density response curves14
MARS via LASSO13
Consistent nonparametric estimation for heavy-tailed sparse graphs13
Locally simultaneous inference13
Minimax optimality of permutation tests12
Infinite-dimensional gradient-based descent for alpha-divergence minimisation12
E-values: Calibration, combination and applications12
The completion of covariance kernels12
An optimal statistical and computational framework for generalized tensor estimation12
Bridging factor and sparse models12
Average treatment effects in the presence of unknown interference12
Testability of high-dimensional linear models with nonsparse structures12
Marginal singularity and the benefits of labels in covariate-shift11
A conformal test of linear models via permutation-augmented regressions11
A Gaussian process approach to model checks11
Sharp global convergence guarantees for iterative nonconvex optimization with random data11
Gaussian approximation for nonstationary time series with optimal rate and explicit construction11
Volatility coupling11
Learning models with uniform performance via distributionally robust optimization11
AutoRegressive approximations to nonstationary time series with inference and applications11
Efficiency in local differential privacy11
Cube root weak convergence of empirical estimators of a density level set10
Semiparametric latent-class models for multivariate longitudinal and survival data10
Optimal change-point detection and localization10
An asymptotic test for constancy of the variance under short-range dependence10
Adaptive test of independence based on HSIC measures10
Factor-driven two-regime regression10
Nonparametric conditional local independence testing10
Graphical models for nonstationary time series10
Editorial: Memorial issue for Charles Stein10
Minimax estimation of smooth densities in Wasserstein distance10
Asymptotic properties of penalized spline estimators in concave extended linear models: Rates of convergence10
High-dimensional inference for dynamic treatment effects9
Asymptotically independent U-statistics in high-dimensional testing9
Bayesian fixed-domain asymptotics for covariance parameters in a Gaussian process model9
Minimax rates for heterogeneous causal effect estimation9
Nonregular and minimax estimation of individualized thresholds in high dimension with binary responses9
Optimal linear discriminators for the discrete choice model in growing dimensions9
On fixed-domain asymptotics, parameter estimation and isotropic Gaussian random fields with Matérn covariance functions9
Asymptotic normality for eigenvalue statistics of a general sample covariance matrix when p/n→∞ and applications8
Early stopping for L2-boosting in high-dimensional linear models8
Correction note: “Asymptotic spectral theory for nonlinear time series”8
Consistent inference for diffusions from low frequency measurements8
Universal Bayes consistency in metric spaces8
The integrated copula spectrum8
Optimal nonparametric testing of Missing Completely At Random and its connections to compatibility8
Distributed estimation and inference for semiparametric binary response models8
Estimating minimum effect with outlier selection8
What is resolution? A statistical minimax testing perspective on superresolution microscopy8
Asymptotic accuracy of the saddlepoint approximation for maximum likelihood estimation8
Asymptotic distributions of high-dimensional distance correlation inference7
Efficiency of delayed-acceptance random walk Metropolis algorithms7
Adaptive and robust multi-task learning7
Inference for low-rank tensors—no need to debias7
Inference on the maximal rank of time-varying covariance matrices using high-frequency data7
Continuous-time targeted minimum loss-based estimation of intervention-specific mean outcomes7
The projected covariance measure for assumption-lean variable significance testing7
Charles Stein and invariance: Beginning with the Hunt–Stein theorem7
Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach7
SuperMix: Sparse regularization for mixtures7
Community detection with dependent connectivity7
Adaptive estimation of multivariate piecewise polynomials and bounded variation functions by optimal decision trees7
Statistical inference for decentralized federated learning7
Frequentist validity of Bayesian limits7
Learning sparse graphons and the generalized Kesten–Stigum threshold7
Limit theorems for distributions invariant under groups of transformations7
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