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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Giulia Vannucci: Learning Global Sensitivity Indices from Observational Data: A Metamodel-Based Approach arxiv.org/abs/2609.40342 arxiv.org/pdf/2609.40342 arxiv.org/html/2609.40342

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Gianmarco Callegher, Miguel de Carvalho: Tail Halos: The Covariate Dual of the Tail arxiv.org/abs/2609.40197 arxiv.org/pdf/2609.40197 arxiv.org/html/2609.40197

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Dimitrios Roxanas: Proximal Empirical Bayes for Sparse Regression with Posterior Decision Support arxiv.org/abs/2609.39983 arxiv.org/pdf/2609.39983 arxiv.org/html/2609.39983

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Marta Bofill Roig, Ekkehard Glimm, Kelly Van Lancker, Martin Posch: Estimands and estimation in trials with time trends arxiv.org/abs/2609.39742 arxiv.org/pdf/2609.39742 arxiv.org/html/2609.39742

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Umberto Picchini: Amortized ratio-estimation importance sampling and localized simulation-based calibration for intractable likelihoods arxiv.org/abs/2609.39712 arxiv.org/pdf/2609.39712 arxiv.org/html/2609.39712

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Christina Schenk, Babak Maboudi Afkham: B-GRASP: A Bayesian Framework for Inferring Graph Weights from SPDE-Inspired Dynamics arxiv.org/abs/2609.39519 arxiv.org/pdf/2609.39519 arxiv.org/html/2609.39519

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Zi Huang, Zhichao Jiang: Policy evaluation and learning with partially identified utility under truncation by death arxiv.org/abs/2609.38783 arxiv.org/pdf/2609.38783 arxiv.org/html/2609.38783

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Kentaro Takeda, Belay B. Yimer, Masahiro Kojima: BOP2-ENR: a Bayesian optimal phase II design for adaptive enrichment with family-wise error rate control and a bound on joint-claim power arxiv.org/abs/2609.38759 arxiv.org/pdf/2609.38759 arxiv.org/html/2609.38759

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Ricardo J. Sandoval, David Arbour, Avi Feller, Michael I. Jordan: Always-On Experimentation arxiv.org/abs/2609.38695 arxiv.org/pdf/2609.38695 arxiv.org/html/2609.38695

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Jim Albert: Batting Average as the Product of Two Rates: Skill, Luck, and the Disappearance of the .400 Hitter arxiv.org/abs/2609.38693 arxiv.org/pdf/2609.38693 arxiv.org/html/2609.38693

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Partha Sarkar, Sairam Rayapolu, Bhargab Chattopadhyay: A Three-Stage PCA Procedure for Sequentially Arriving High-Dimensional Data arxiv.org/abs/2609.38681 arxiv.org/pdf/2609.38681 arxiv.org/html/2609.38681

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Hanqing Li, Yaroslav Golub, Xuewen Lu: Adaptive mixture variational inference for spike-and-slab regression arxiv.org/abs/2609.38656 arxiv.org/pdf/2609.38656 arxiv.org/html/2609.38656

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Kendall Thomas, Jan Hannig: Generalized Fiducial Inference for Hybrid Discrete-Continuous Count Data: Theory and Application arxiv.org/abs/2609.38611 arxiv.org/pdf/2609.38611 arxiv.org/html/2609.38611

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Bourazas, Alexopoulos, Dellaportas, Kalogeropoulos: Fraud Detection via Bayesian Positive--Unlabeled Learning with Gaussian Processes and Multilayer Networks arxiv.org/abs/2609.38586 arxiv.org/pdf/2609.38586 arxiv.org/html/2609.38586

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Massimiliano Russo, Georg Hahn, Krista F. Huybrechts, Shirley V. Wang: A tree-based scan statistic for database studies with time-to-event outcomes arxiv.org/abs/2609.38582 arxiv.org/pdf/2609.38582 arxiv.org/html/2609.38582

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Larry F. Leon, Keaven M. Anderson: Inference for Standard Trial Estimands after Data-Driven Subgroup Discovery arxiv.org/abs/2609.38361 arxiv.org/pdf/2609.38361 arxiv.org/html/2609.38361

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

Yuta Nonomiya, Kazuki Nishida: Small-study effects on the hierarchical summary ROC curve: latent accuracy and threshold trends in meta-analysis of diagnostic test accuracy arxiv.org/abs/2609.38297 arxiv.org/pdf/2609.38297 arxiv.org/html/2609.38297

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arXiv stat.ME Methodology @statme-bot.bsky.social · 6h

[2026-10-01 Thu (UTC), 18 new articles found for statME Methodology]

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Grace V. Ringlein, Trang Q. Nguyen, Elizabeth A. Stuart, Harsh Parikh: Proximal causal inference through cross-proxy balancing arxiv.org/abs/2609.38175 arxiv.org/pdf/2609.38175 arxiv.org/html/2609.38175

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Runbing Zheng, Dmitriy Kunisky: Global Synchronization for Multi-Source Data Integration under Blockwise Missing Patterns arxiv.org/abs/2609.38141 arxiv.org/pdf/2609.38141 arxiv.org/html/2609.38141

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Xinyue Xu, Mengtao Wen, Long Feng: Two-sample tests for principal eigenvalues and eigenvectors in high-dimensional elliptical factor models arxiv.org/abs/2609.37906 arxiv.org/pdf/2609.37906 arxiv.org/html/2609.37906

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Subir Hait: Target-Aware Sequential Inference: Pooled versus Stratified Anytime-Valid Designs arxiv.org/abs/2609.37873 arxiv.org/pdf/2609.37873 arxiv.org/html/2609.37873

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Keith Barnatchez, Willow Butler, Julia A. Geller, Elizabeth A. Stuart: Characterizing Survivor Principal Strata Over Time: Identification, Efficient Estimation, and Sensitivity Analysis arxiv.org/abs/2609.37821 arxiv.org/pdf/2609.37821 arxiv.org/html/2609.37821

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Rares Dimitrie Grozavescu, Mark Girolami: When Noise Estimation Hides Basis Misspecification in Repeated Bayesian Inverse Problems arxiv.org/abs/2609.37762 arxiv.org/pdf/2609.37762 arxiv.org/html/2609.37762

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Songqiao Han, Kalliopi Mylona, Steven Gilmour, Matteo Borrotti: Sequential Supersaturated Screening Experiments arxiv.org/abs/2609.37756 arxiv.org/pdf/2609.37756 arxiv.org/html/2609.37756

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Xingwei Liu, Yuhong Yang, Wangli Xu: SPARK: A General Goodness-of-Fit Assessment via Residual Projection arxiv.org/abs/2609.37705 arxiv.org/pdf/2609.37705 arxiv.org/html/2609.37705

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Muluneh Alene, Kelly Van Lancker, Stijn Vansteelandt: On the use of G-computation in small randomized controlled trials with many covariates arxiv.org/abs/2609.37630 arxiv.org/pdf/2609.37630 arxiv.org/html/2609.37630

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Tomoshige Nakamura, Ryo Emoto: Debiased and Simultaneous Inference for Heterogeneous Factorial Effect Modifiers via Residualized Walsh-Hadamard Scores arxiv.org/abs/2609.37382 arxiv.org/pdf/2609.37382 arxiv.org/html/2609.37382

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Cici Chen Gu, Eszter Lakatos, Sara Hamis: The MCMC convergence graph: a diagnostic for multimodal posteriors arxiv.org/abs/2609.37352 arxiv.org/pdf/2609.37352 arxiv.org/html/2609.37352

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Fernando Pires Hartwig, George Davey Smith, Frank Dudbridge, Jack Bowden: The INSIDE assumption under all positive coding: interpretation and partial empirical assessment arxiv.org/abs/2609.37347 arxiv.org/pdf/2609.37347 arxiv.org/html/2609.37347

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Zhan Gao, Danyang Huang, Rui Pan, Hansheng Wang: Popularity Regression-Based Latent Space Model for Large-Scale Sparse Network Analysis arxiv.org/abs/2609.37284 arxiv.org/pdf/2609.37284 arxiv.org/html/2609.37284

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Zhongze Cai, Martin B. Haugh, Xiaocheng Li: When Stress Tests Miss the Risk: Statistical Scenario Analysis for Financial Portfolios arxiv.org/abs/2609.37273 arxiv.org/pdf/2609.37273 arxiv.org/html/2609.37273

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Jinxiu Wen, Zhiming Li: Bayesian inference of risk differences for multi-group bilateral data arxiv.org/abs/2609.37251 arxiv.org/pdf/2609.37251 arxiv.org/html/2609.37251

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Adam Bilchouris, Andriy Olenko: CovEsts: Nonparametric Autocovariance Estimation and Analysis arxiv.org/abs/2609.37154 arxiv.org/pdf/2609.37154 arxiv.org/html/2609.37154

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Enock Adu Bonsu: A statistical framework for identifying subgroup vulnerability to predictive multiplicity in clinical AI arxiv.org/abs/2609.37064 arxiv.org/pdf/2609.37064 arxiv.org/html/2609.37064

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Yulong Li, Ke Wan, Toshio Shimokawa, Kensuke Tanioka: BRP-GABLE: An Interpretable Rule-Based Prediction Framework for Multiple Outcome Types arxiv.org/abs/2609.36839 arxiv.org/pdf/2609.36839 arxiv.org/html/2609.36839

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Shahid Khan, Andriy Olenko: Testing Diagonal Anisotropy Based on Single Realisation of Spherical Random Field arxiv.org/abs/2609.36786 arxiv.org/pdf/2609.36786 arxiv.org/html/2609.36786

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

John Boland, Matthias Fresacher, David Hill, Shijia Jin, Ya Li, Graham Mills, Kihun Nam, Craig Oakeshotte, Andriy Olenko: Measures of Reliability Risk for the Australian Energy Sector arxiv.org/abs/2609.36751 arxiv.org/pdf/2609.36751 arxiv.org/html/2609.36751

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Xiaokai Luo, Chenghao Xu, Haotian Xu, Carlos Misael Madrid Padilla, Daren Wang: Optimal detection of general moment changes: Simultaneous mean and covariance change detection and beyond arxiv.org/abs/2609.36594 arxiv.org/pdf/2609.36594 arxiv.org/html/2609.36594

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Gefei Lin, Rui Miao, Xiaoke Zhang: Finite-Sample Theory for Fitted Q-Iteration When Actions Are Functions arxiv.org/abs/2609.36390 arxiv.org/pdf/2609.36390 arxiv.org/html/2609.36390

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Shuoyang Wang, Wanyu Zhang, Lingli Yang, Kexuan Li: Adaptive Sampling of Costly Outcomes in Randomized Clinical Trials arxiv.org/abs/2609.36387 arxiv.org/pdf/2609.36387 arxiv.org/html/2609.36387

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Yeseul Jeon, Aaron Scheffler, Rajarshi Guhaniyogi: MCMC-Free Uncertainty Quantification for Deep Generative Inference for Spatially Varying Coefficient Models at Scale arxiv.org/abs/2609.36325 arxiv.org/pdf/2609.36325 arxiv.org/html/2609.36325

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Paul T. von Hippel: Faster Estimates from Binned Test Score Data---and How Accurate They Are arxiv.org/abs/2609.36312 arxiv.org/pdf/2609.36312 arxiv.org/html/2609.36312

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Danna L. Cruz-Reyes, Juan Sosa, Carlos A. Mart\'inez: Bayesian Selection of Edge Spectral Modes for Crash Counts on Urban Road Networks with Applications in Barcelona and Bogot\'a arxiv.org/abs/2609.36268 arxiv.org/pdf/2609.36268 arxiv.org/html/2609.36268

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Joshua Chen, Peter Jan van Leeuwen: Copula Active Subspaces I: A Score-Covariance Method for Reduced-Order Non-Gaussian Density Estimation arxiv.org/abs/2609.36142 arxiv.org/pdf/2609.36142 arxiv.org/html/2609.36142

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Danhyang Lee, Shinyoung Jeon, Shu Yang: Bridge-Anchored Partial Identification of a Target Mean under Outcome-Model Drift arxiv.org/abs/2609.36132 arxiv.org/pdf/2609.36132 arxiv.org/html/2609.36132

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arXiv stat.ME Methodology @statme-bot.bsky.social · 30/09/2026

Shuren He, Huiyan Sang, Ligang Lu: Graph-Split Bayesian Causal Forest for Spatial Heterogeneous Treatment Effect Estimation arxiv.org/abs/2609.36046 arxiv.org/pdf/2609.36046 arxiv.org/html/2609.36046

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