Probability & Statistics · Mathematics & Statistics
Statistics Theory
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321 papers, from 31 August 2026 to 4 November 2026: 287 arXiv preprints and 34 OpenAlex records.
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Newest papers, page 15
A Unifying Perspective on Probabilities as Model Predictions
Although probabilistic statements are ubiquitous, foundational disagreements persist about their understanding, as exemplified by debates between Bayesians and frequentists; moreover, it is unclear…Algorithmic stability via ensembling
Algorithmic stability refers to the property of an algorithm being insensitive to perturbations of the input data, where the type of perturbation may vary depending on the setting.The Elliptically Optimal Confidence Interval: A Bivariate Extension of Wilson's Score Method
Constructing a confidence interval for the difference between two independent binomial proportions involves a nuisance direction that is not identified by the estimand.Non-Adaptive 1-Bit Mean Estimation: Minimax Rates and the Sample-Interval Tradeoff
We study distributed one-dimensional mean estimation under a 1-bit communication constraint.High-Magnetization Sampling at Low Temperatures: Ising Models and Bayesian Sparse Linear Regression
Sparsity is a powerful structural resource in optimization and statistics.MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra
Minimum-norm confidence envelope strategies offer a nonparametric approach to constructing nonasymptotic, simultaneous confidence regions for band-limited functions, exploiting the theory of…Entropy bounds and global couplings for union-closed families
We give a computer-assisted proof that every finite union-closed family containing a nonempty set has an element in at least 0.38288525 of its members.Accelerated High-Accuracy Sampling from a Warm Start via the Proximal Bouncy Particle Sampler
We study the problem of sampling from $μ(\mathrm{d}x)\propto e^{-V(x)}\,\mathrm{d}x$ on $\mathbb{R}^d$, where $V$ is $α$-strongly convex and $β$-smooth, and write $κ:=β/α$.Smoothed Picard Hamiltonian Monte Carlo
We develop a new low-accuracy sampler, called \emph{smoothed Picard Hamiltonian Monte Carlo}, which combines Gaussian smoothing, Picard iteration, and higher-order discretization.Almost Sharp Equivalence between Approximate Message Passing and Low-Degree Polynomials
We prove a sharp lower bound for growing-degree polynomial estimation in the Gaussian planted submatrix model.Tensor network representations of discrete maximum entropy distributions via mean polytopes
We present tensor network representations for discrete maximum entropy distributions under expectation constraints.Adaptive Conformal Inference Under Delayed Feedback: Coverage Guarantees and a Delay-to-Memory Diagnostic
Adaptive Conformal Inference (ACI) extends conformal prediction to non-exchangeable settings by adjusting the nominal miscoverage level online in response to recent coverage errors.Sharp Structure-Agnostic Minimax Risk for Partial Linear Models
We characterize the sharp structure-agnostic minimax risk for coefficient estimation in the partial linear model when the outcome and treatment nuisances are learned by two distinct black-box…Efficient model exploration with the integrated nested Laplace approximation
Model and variable selection are important topics in Bayesian inference.Two-resolution state modelling of intermittent online gambling activity during Sweden's temporary deposit-cap period
Intermittent online gambling records create two distinct representation problems: calendar-time analyses must retain represented days with no recorded play, whereas analyses of active behaviour must…Cluster-Based Dimensionality Reduction by Nonparametric Distributional Screening
We consider dimensionality reduction for high-dimensional observations accompanied by a supplied partition into two or more clusters.Diagonal Attenuation: A Finite-Sample Correction for PCA
Principal component analysis (PCA) can rotate away from its population target when a covariance matrix is estimated from limited data.A Gamma envelope and sharp moment inequalities for Gaussian quadratic forms
We study extremal absolute central moments of Gaussian quadratic forms under a fixed Frobenius norm.Faster Learning under Relaxed Local Differential Privacy
We consider density estimation under the relaxed local differential privacy condition that the privatized distributions are $α$-close in total variation distance.Reconciling Universal and Uniform Learning with $Q$-Aggregation
We study regression under bounded responses in terms of excess mean squared error.