Annals of Statistics

Papers
(The median citation count of Annals of Statistics is 2. 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 2021-04-01 to 2025-04-01.)
ArticleCitations
Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences127
On singular values of data matrices with general independent columns79
Optimal estimation and computational limit of low-rank Gaussian mixtures66
Ridge regression revisited: Debiasing, thresholding and bootstrap64
Change-point analysis with irregular signals62
Online inference with multi-modal likelihood functions61
On the approximation accuracy of Gaussian variational inference61
Statistical inference for rough volatility: Minimax theory59
One-step estimation of differentiable Hilbert-valued parameters46
Online change-point detection for matrix-valued time series with latent two-way factor structure44
Generalization error bounds of dynamic treatment regimes in penalized regression-based learning41
Foundations of structural causal models with cycles and latent variables33
Orthogonal statistical learning33
Maximum likelihood for high-noise group orbit estimation and single-particle cryo-EM31
High-dimensional nonparametric density estimation via symmetry and shape constraints30
Inference in Ising models on dense regular graphs27
Extreme value inference for heterogeneous power law data27
False discovery rate control with unknown null distribution: Is it possible to mimic the oracle?27
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes27
Dispersal density estimation across scales27
Parametric copula adjusted for non- and semiparametric regression26
Carving model-free inference25
Off-policy evaluation in partially observed Markov decision processes under sequential ignorability24
The Stein effect for Fréchet means24
A cross-validation framework for signal denoising with applications to trend filtering, dyadic CART and beyond24
Principal components in linear mixed models with general bulk24
Scalable estimation and inference for censored quantile regression process24
MARS via LASSO22
On the disjoint and sliding block maxima method for piecewise stationary time series21
Adaptive estimation in multivariate response regression with hidden variables21
Locally simultaneous inference21
Metric statistics: Exploration and inference for random objects with distance profiles21
Robust k-means clustering for distributions with two moments21
The adaptive Wynn algorithm in generalized linear models with univariate response20
A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids20
Large-scale inference with block structure19
Estimation and inference for minimizer and minimum of convex functions: Optimality, adaptivity and uncertainty principles19
Optimization hierarchy for fair statistical decision problems19
Optimal disclosure risk assessment19
Half-trek criterion for identifiability of latent variable models18
Choosing between persistent and stationary volatility17
ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM17
Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators17
Convergence rates of oblique regression trees for flexible function libraries16
On universally consistent and fully distribution-free rank tests of vector independence16
Boosted nonparametric hazards with time-dependent covariates16
Parameter estimation in nonlinear multivariate stochastic differential equations based on splitting schemes16
Variable selection consistency of Gaussian process regression16
On the sample complexity of entropic optimal transport15
On high-dimensional Poisson models with measurement error: Hypothesis testing for nonlinear nonconvex optimization15
Nonlinear global Fréchet regression for random objects via weak conditional expectation15
Empirical partially Bayes multiple testing and compound χ2 decisions15
Tensor clustering with planted structures: Statistical optimality and computational limits15
A statistical framework of watermarks for large language models: Pivot, detection efficiency and optimal rules15
Measuring dependence in the Wasserstein distance for Bayesian nonparametric models14
On an extension of the promotion time cure model14
Minimax optimality of permutation tests14
Stein’s method of normal approximation: Some recollections and reflections14
Testability of high-dimensional linear models with nonsparse structures14
Infinite-dimensional gradient-based descent for alpha-divergence minimisation14
Universal rank inference via residual subsampling with application to large networks14
Adaptive robust estimation in sparse vector model14
The completion of covariance kernels14
Consistent nonparametric estimation for heavy-tailed sparse graphs13
Marginal singularity and the benefits of labels in covariate-shift13
Nonparametric Bayesian inference for reversible multidimensional diffusions13
Learning models with uniform performance via distributionally robust optimization12
Gaussian approximation for nonstationary time series with optimal rate and explicit construction12
Deep learning for the partially linear Cox model12
A Gaussian process approach to model checks12
A conformal test of linear models via permutation-augmented regressions12
An optimal statistical and computational framework for generalized tensor estimation12
Efficiency in local differential privacy12
Sharp global convergence guarantees for iterative nonconvex optimization with random data12
Bridging factor and sparse models11
E-values: Calibration, combination and applications11
Semiparametric latent-class models for multivariate longitudinal and survival data11
Conformal prediction beyond exchangeability11
AutoRegressive approximations to nonstationary time series with inference and applications11
Average treatment effects in the presence of unknown interference11
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression11
Distribution and quantile functions, ranks and signs in dimension d: A measure transportation approach11
Asymptotic accuracy of the saddlepoint approximation for maximum likelihood estimation10
The projected covariance measure for assumption-lean variable significance testing10
Factor-driven two-regime regression10
Optimal nonparametric testing of Missing Completely At Random and its connections to compatibility10
Nonparametric conditional local independence testing10
Volatility coupling10
Rate-optimal cluster-randomized designs for spatial interference10
Correction note: “Asymptotic spectral theory for nonlinear time series”10
Editorial: Memorial issue for Charles Stein10
Cube root weak convergence of empirical estimators of a density level set9
Adaptive estimation of multivariate piecewise polynomials and bounded variation functions by optimal decision trees9
Bayesian fixed-domain asymptotics for covariance parameters in a Gaussian process model9
Charles Stein and invariance: Beginning with the Hunt–Stein theorem9
On fixed-domain asymptotics, parameter estimation and isotropic Gaussian random fields with Matérn covariance functions9
Adaptive and robust multi-task learning9
What is resolution? A statistical minimax testing perspective on superresolution microscopy8
Density deconvolution under general assumptions on the distribution of measurement errors8
Statistical inference for decentralized federated learning8
A general characterization of optimal tie-breaker designs8
Graphical models for nonstationary time series8
Estimation of mixed fractional stable processes using high-frequency data8
Asymptotic properties of penalized spline estimators in concave extended linear models: Rates of convergence8
Settling the sample complexity of model-based offline reinforcement learning8
Analysis of “learn-as-you-go” (LAGO) studies8
An asymptotic test for constancy of the variance under short-range dependence8
Nonregular and minimax estimation of individualized thresholds in high dimension with binary responses7
Early stopping for L2-boosting in high-dimensional linear models7
Universal Bayes consistency in metric spaces7
Inference on the maximal rank of time-varying covariance matrices using high-frequency data7
Minimax rates for heterogeneous causal effect estimation7
Consistent inference for diffusions from low frequency measurements7
Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach7
Optimal linear discriminators for the discrete choice model in growing dimensions7
High-dimensional inference for dynamic treatment effects7
Linearized two-layers neural networks in high dimension7
Asymptotic normality for eigenvalue statistics of a general sample covariance matrix when p/n→∞ and applications7
Learning sparse graphons and the generalized Kesten–Stigum threshold7
Minimax estimation of smooth densities in Wasserstein distance6
Asymptotic analysis of synchrosqueezing transform—toward statistical inference with nonlinear-type time-frequency analysis6
Existence and uniqueness of the Kronecker covariance MLE6
Approximate and exact designs for total effects6
Optimality of spectral clustering in the Gaussian mixture model6
Statistical inference for principal components of spiked covariance matrices6
Improved central limit theorem and bootstrap approximations in high dimensions6
Integrative methods for post-selection inference under convex constraints6
How do noise tails impact on deep ReLU networks?6
Efficiency of delayed-acceptance random walk Metropolis algorithms6
The interpolation phase transition in neural networks: Memorization and generalization under lazy training6
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization6
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA6
Inference for low-rank models6
Joint sequential detection and isolation for dependent data streams6
Adaptive test of independence based on HSIC measures6
SuperMix: Sparse regularization for mixtures6
Limit theorems for distributions invariant under groups of transformations6
Uniform convergence of local Fréchet regression with applications to locating extrema and time warping for metric space valued trajectories6
Admissible ways of merging p-values under arbitrary dependence6
Testing high-dimensional regression coefficients in linear models6
Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences6
Rate-optimal estimation of mixed semimartingales5
Distributed estimation and inference for semiparametric binary response models5
The integrated copula spectrum5
Asymptotic distributions of high-dimensional distance correlation inference5
Computational barriers to estimation from low-degree polynomials5
Inference for low-rank tensors—no need to debias5
Optimal discriminant analysis in high-dimensional latent factor models5
Computationally efficient and statistically optimal robust high-dimensional linear regression5
Precise statistical analysis of classification accuracies for adversarial training5
Reconciling design-based and model-based causal inferences for split-plot experiments5
Optimal change-point detection and localization5
Matching recovery threshold for correlated random graphs5
Efficient functional estimation and the super-oracle phenomenon5
Ensemble projection pursuit for general nonparametric regression5
Community detection with dependent connectivity5
Continuous-time targeted minimum loss-based estimation of intervention-specific mean outcomes5
On cross-validated Lasso in high dimensions5
Coverage of credible intervals in Bayesian multivariate isotonic regression5
Consistent order selection for ARFIMA processes4
Is infinity that far? A Bayesian nonparametric perspective of finite mixture models4
The impacts of unobserved covariates on covariate-adaptive randomized experiments4
Local Whittle estimation of high-dimensional long-run variance and precision matrices4
Testing goodness-of-fit and conditional independence with approximate co-sufficient sampling4
Statistical guarantees for Bayesian uncertainty quantification in nonlinear inverse problems with Gaussian process priors4
A nonparametric doubly robust test for a continuous treatment effect4
Minimax rates in sparse, high-dimensional change point detection4
Optimal estimation of high-dimensional Gaussian location mixtures4
Willem van Zwet, teacher and thesis advisor4
Canonical thresholding for nonsparse high-dimensional linear regression4
All-in-one robust estimator of the Gaussian mean4
Safe adaptive importance sampling: A mixture approach4
Peskun–Tierney ordering for Markovian Monte Carlo: Beyond the reversible scenario4
On posterior consistency of data assimilation with Gaussian process priors: The 2D-Navier–Stokes equations4
Sparse high-dimensional linear regression. Estimating squared error and a phase transition4
A causal bootstrap4
Debiasing convex regularized estimators and interval estimation in linear models4
Posterior analysis of n in the binomial (n,p) problem with both parameters unknown—with applications to quantitative nanoscopy4
Limiting distributions for eigenvalues of sample correlation matrices from heavy-tailed populations4
Bootstrapping persistent Betti numbers and other stabilizing statistics4
Refined Cramér-type moderate deviation theorems for general self-normalized sums with applications to dependent random variables and winsorized mean4
Optimal estimation of Schatten norms of a rectangular matrix4
Affine-equivariant inference for multivariate location under Lp loss functions4
Coverage of credible intervals in nonparametric monotone regression4
A CLT for second difference estimators with an application to volatility and intensity3
On the robustness of minimum norm interpolators and regularized empirical risk minimizers3
A no-free-lunch theorem for multitask learning3
Spectral statistics of sample block correlation matrices3
Post-selection inference via algorithmic stability3
On extended admissible procedures and their nonstandard Bayes risk3
The online closure principle3
Minimax rates for conditional density estimation via empirical entropy3
Pattern graphs: A graphical approach to nonmonotone missing data3
Optimal difference-based variance estimators in time series: A general framework3
Heavy-tailed Bayesian nonparametric adaptation3
Analysis of generalized Bregman surrogate algorithms for nonsmooth nonconvex statistical learning3
Environment invariant linear least squares3
Efficient estimation of the maximal association between multiple predictors and a survival outcome3
A convex optimization approach to high-dimensional sparse quadratic discriminant analysis3
Construction of mixed orthogonal arrays with high strength3
Optimal policy evaluation using kernel-based temporal difference methods3
Exact minimax optimality of spectral methods in phase synchronization and orthogonal group synchronization3
Reconciling the Gaussian and Whittle likelihood with an application to estimation in the frequency domain3
Rerandomization with diminishing covariate imbalance and diverging number of covariates3
Isotonic regression with unknown permutations: Statistics, computation and adaptation3
Necessary and sufficient conditions for variable selection consistency of the LASSO in high dimensions3
Spectral estimation of Hawkes processes from count data3
On robustness and local differential privacy3
Local permutation tests for conditional independence3
Multivariate trend filtering for lattice data3
Total positivity in exponential families with application to binary variables3
A general framework to quantify deviations from structural assumptions in the analysis of nonstationary function-valued processes3
Sharp optimality for high-dimensional covariance testing under sparse signals3
Random graph asymptotics for treatment effect estimation under network interference3
Optimal high-dimensional and nonparametric distributed testing under communication constraints3
Rank and factor loadings estimation in time series tensor factor model by pre-averaging3
A power analysis for model-X knockoffs with ℓp-regularized statistics3
Nonparametric bivariate density estimation for censored lifetimes3
The edge of discovery: Controlling the local false discovery rate at the margin3
Characterizing the SLOPE trade-off: A variational perspective and the Donoho–Tanner limit3
Single index Fréchet regression3
Adaptive variational Bayes: Optimality, computation and applications3
Global and individualized community detection in inhomogeneous multilayer networks3
Supervised homogeneity fusion: A combinatorial approach3
Simultaneous statistical inference for second order parameters of time series under weak conditions3
Order-of-addition orthogonal arrays to study the effect of treatment ordering3
Breaking the winner’s curse in Mendelian randomization: Rerandomized inverse variance weighted estimator2
General and feasible tests with multiply-imputed datasets2
Willem van Zwet’s contributions to the profession2
Optimal false discovery rate control for large scale multiple testing with auxiliary information2
Wilks’ theorem for semiparametric regressions with weakly dependent data2
Iterative algorithm for discrete structure recovery2
Uniform consistency in nonparametric mixture models2
Tensor-on-tensor regression: Riemannian optimization, over-parameterization, statistical-computational gap and their interplay2
Differentially private inference via noisy optimization2
New Edgeworth-type expansions with finite sample guarantees2
Doubly debiased lasso: High-dimensional inference under hidden confounding2
Adaptive learning rates for support vector machines working on data with low intrinsic dimension2
On statistical learning of simplices: Unmixing problem revisited2
Assigning topics to documents by successive projections2
Two-level parallel flats designs2
Some theory about efficient dimension reduction regarding the interaction between two responses2
A nonparametric test for elliptical distribution based on kernel embedding of probabilities2
Estimation of smooth functionals in normal models: Bias reduction and asymptotic efficiency2
Empirical tail copulas for functional data2
Locally associated graphical models and mixed convex exponential families2
General spatio-temporal factor models for high-dimensional random fields on a lattice2
Empirical likelihood based testing for multivariate regular variation2
Characterization of causal ancestral graphs for time series with latent confounders2
Time-uniform, nonparametric, nonasymptotic confidence sequences2
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