Clay weekly context brief for the Statistics category (ISO week 2026-W43).

Clay tracks publications from the Statistics feed list. Below are recent items from this category, each with its source and a short description of what the publication covers when one is available in the source feed.

Recent publications:
1. GeoMix: A Bayesian Framework for Stratigraphic and Geotechnical Inference
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2610.21021
   Accurate characterisation of subsea sediments is essential for engineering projects such as offshore wind farms, but the challenging environment and large spatial domains involved make dense geotechnical measurements impractical.
2. Clinically Interpretable Biological Age Estimation Using CatBoost and SHAP with Continuous and Categorical Features from NHANES
   Source: stat.CO (Computation)
   Link: https://arxiv.org/abs/2610.20868
   Biological age (BA) captures inter-individual variation in physiological aging beyond chronological age (CA).
3. Latent Annealed Posterior Sampling with a Variance-Preserving Bridge for Sparsely Observed Random Fields
   Source: stat.ML (Machine Learning)
   Link: https://arxiv.org/abs/2610.20659
   Posterior inference for random fields from sparse observations presents two major challenges: accurately characterizing complex spatial uncertainty and preventing conditional sampling costs from growing substantially as the spatial grid is refined.
4. Principal component error in high-dimensional factor models
   Source: stat.TH (Statistics Theory)
   Link: https://arxiv.org/abs/2609.20550
   In a statistical factor model, principal components (or eigenvectors) of a sample covariance matrix serve as estimates of principal directions, the true drivers of co-movement of a collection of observed variables.
5. Living Synthetic Benchmarks: A Neutral and Cumulative Framework for Simulation Studies
   Source: stat.ME (Methodology)
   Link: https://arxiv.org/abs/2510.19489
   Simulation studies are widely used to evaluate statistical methods.
6. Beyond Match Results: Bayesian Mediation of Ability, Performance, and Winning in Professional Tennis
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2610.21023
   Match results measure competitive ability, but they do not explain how ability is expressed during play.
7. Amortized ratio-estimation importance sampling and localized simulation-based calibration for intractable likelihoods
   Source: stat.CO (Computation)
   Link: https://arxiv.org/abs/2609.39712
   We consider simulation-based Bayesian inference (SBI) for the parameters of models with intractable likelihoods but tractable forward simulation.
8. Graph Additive Models disentangling feature, topology, and interactions
   Source: stat.ML (Machine Learning)
   Link: https://arxiv.org/abs/2610.20662
   Graph Neural Additive Networks (GNANs) have emerged as effective, interpretable-by-design architectures for graph learning.
9. Ultra-high-dimensional spot support screening in continuous-time regression
   Source: stat.TH (Statistics Theory)
   Link: https://arxiv.org/abs/2608.08582
   We study variable screening for high-frequency continuous-time regression, targeting the support of the spot regression coefficient.
10. Density Discontinuity Regression
   Source: stat.ME (Methodology)
   Link: https://arxiv.org/abs/2507.05581
   Many policies hinge on a continuous variable exceeding a threshold, prompting strategic behavior by agents to stay on the favorable side.
11. Reliability and Preventive Maintenance for Multivariate Gamma Degradation with Shared Random Effects and Cumulative Environmental Shock Damage
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2610.21079
   In industrial engineering, many highly reliable products have multiple performance characteristics that degrade simultaneously over time.
12. Shortest fixed-width confidence intervals for a bounded parameter: The Push algorithm
   Source: stat.CO (Computation)
   Link: https://arxiv.org/abs/2511.13694
   We present a method for computing optimal fixed-width confidence intervals for a single, bounded parameter, extending a method for the binomial due to Asparaouhov and Lorden, who called it the Push algorithm.
13. On the Stability and Convergence of Flow Map Training
   Source: stat.ML (Machine Learning)
   Link: https://arxiv.org/abs/2610.20674
   Flow maps are a recent method of probabilistic generation that amortize diffusion trajectories into one-step samplers, unlocking efficient generation.
14. Optimal score function estimation via derivatives constraints
   Source: stat.TH (Statistics Theory)
   Link: https://arxiv.org/abs/2606.19084
   We provide a statistical theory explaining why empirical score matching can achieve minimax optimal performance for diffusion generative models when the data distribution is supported on a low-dimensional manifold.
15. Measuring frailty in the elderly: an indicator based on a super-classifier
   Source: stat.ME (Methodology)
   Link: https://arxiv.org/abs/2506.22349
   Identifying frail older adults in an ageing population is essential for improving healthcare services.
16. Trial design considerations in the face of overdispersion and time-varying event rates: a meta-regression approach with an application in asthma
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2610.21432
   **Purpose:** Relative changes in event rates are a common primary endpoint in confirmatory asthma trials.
17. Stereographic Multiple-Try Metropolis
   Source: stat.CO (Computation)
   Link: https://arxiv.org/abs/2505.12487
   Multiple-proposal MCMC algorithms have recently gained attention for their potential to improve performance, especially through parallel implementation on modern hardware.
18. Complete or Sparse: A Tale of Two Identifiabilities
   Source: stat.ML (Machine Learning)
   Link: https://arxiv.org/abs/2610.20851
   Understanding when neural networks learn interpretable representations is central to mechanistic interpretability.
19. Smooth Hard-Thresholding for Singular Values with Stein's Unbiased Risk Estimate
   Source: stat.TH (Statistics Theory)
   Link: https://arxiv.org/abs/2606.06632
   Low-rank matrix denoising is a central primitive in patch-based image restoration and many other inverse problems.
20. Controlling the false discovery rate in high-dimensional linear models using model-X knockoffs and $p$-values
   Source: stat.ME (Methodology)
   Link: https://arxiv.org/abs/2505.16124
   We propose a novel multiple testing methodology for controlling the false discovery rate (FDR) in high-dimensional linear models that integrates model-X knockoff techniques with debiased penalized regression estimators.
21. Contact, Power, and Balls in Play: A Three-Rate Decomposition of Batting Average and the Disappearance of the .400 Hitter
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2610.21836
   Batting average factors exactly as BA = c [h + (1-h) b], where c is the rate of avoiding a strikeout, h is the home-run rate among non-strikeout at-bats, and b is batting average on balls in play (BABIP).
22. Multivariate L\'evy Adaptive B-Spline Regression
   Source: stat.CO (Computation)
   Link: https://arxiv.org/abs/2108.11863
   We propose Multivariate L\'evy Adaptive B-Spline Regression (MLABS), a Bayesian nonparametric regression model designed to capture nonlinear effects, interactions, and locally varying features of multivariate functions.
23. Time-partitioning Gaussian Process Mixture Model
   Source: stat.ML (Machine Learning)
   Link: https://arxiv.org/abs/2610.20860
   We propose the Time-partitioning Gaussian Process Mixture Model (TPGPMM), a Bayesian nonparametric framework for identifying persistent regimes and modelling nonstationary dependence in time series.
24. Robustness for free: asymptotic size and power of max-tests in high dimensions
   Source: stat.TH (Statistics Theory)
   Link: https://arxiv.org/abs/2601.14013
   Allowing for adversarial contamination and heavy tails, we study testing whether the mean of a high-dimensional random vector equals zero.
25. Multi-Sensitive Distributional Fairness: Joint Wasserstein Audits and Shapley Allocation
   Source: stat.ME (Methodology)
   Link: https://arxiv.org/abs/2610.19252
   Fairness audits with several sensitive attributes are often performed one coordinate at a time.
26. A Bayesian Spatially Varying Coefficient Model for Surface Urban Heat Island Estimation
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2610.21980
   Surface urban heat islands (SUHIs) are commonly studied using satellite-derived land surface temperature (LST), but many analyses rely on static summaries or pointwise urban-rural contrasts, providing limited inference on temporal change, spatial dependence, and uncertainty.
27. On Complexity of Gaussian Sampling
   Source: stat.CO (Computation)
   Link: https://arxiv.org/abs/2610.20492
   We study the number of exact matrix-vector queries needed to sample a centered $d$-dimensional Gaussian with condition number at most $\kappa$ to total variation error $\varepsilon$.
28. Flexible Doubly Robust Proximal Causal Inference for Censored Outcomes
   Source: stat.ML (Machine Learning)
   Link: https://arxiv.org/abs/2610.20893
   Estimating causal effects on right-censored time-to-event outcomes is challenging under unmeasured confounding.
29. Spectral estimation for high-dimensional linear processes
   Source: stat.TH (Statistics Theory)
   Link: https://arxiv.org/abs/2504.10257
   We develop a random-matrix-based framework for estimating the latent joint spectral distribution of the coefficient matrices and innovation covariance of a class of high-dimensional linear processes from the eigenvalues of weighted sample periodograms.
30. Generalizing Identifiability Results in Causal Discovery from Complete Data to Missing Data Settings
   Source: stat.ME (Methodology)
   Link: https://arxiv.org/abs/2610.19211
   While causal discovery methods have matured for complete data, such algorithms for handling missing values remain limited.
31. The Reach of Treatment Effects: Randomization Inference for Zero-Effect Regions
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2610.20759
   A treatment may affect some individuals while leaving others unaffected.

Sources in this brief: stat.AP (Applications); stat.CO (Computation); stat.ME (Methodology); stat.ML (Machine Learning); stat.TH (Statistics Theory).
Selected 31 of 390 available items for this weekly brief.