arXiv stat.ME Methodology

Abhik Ghosh, Suryasis Jana: Provably robust learning of regression neural networks using $\beta$-divergences https://arxiv.org/abs/2602.08933 https://arxiv.org/pdf/2602.08933 https://arxiv.org/html/2602.08933

Rohan Hore, Ruodu Wang, Aaditya Ramdas: Online monotone density estimation and log-optimal calibration https://arxiv.org/abs/2602.08927 https://arxiv.org/pdf/2602.08927 https://arxiv.org/html/2602.08927

Xiaotong Liu, Shao-Bo Lin, Jun Fan, Ding-Xuan Zhou: Two-Stage Data Synthesization: A Statistics-Driven Restricted Trade-off between Privacy and Prediction https://arxiv.org/abs/2602.08657 https://arxiv.org/pdf/2602.08657 https://arxiv.org/html/2602.08657

Yash Patel, Ambuj Tewari: Distribution-Free Robust Functional Predict-Then-Optimize https://arxiv.org/abs/2602.08215 https://arxiv.org/pdf/2602.08215 https://arxiv.org/html/2602.08215

Cristian Minoccheri, Sophia Tesic, Kayvan Najarian, Ryan Stidham: A Causal Machine Learning Framework for Treatment Personalization in Clinical Trials: Application to Ulcerative Colitis https://arxiv.org/abs/2602.08171 https://arxiv.org/pdf/2602.08171 https://arxiv.org/html/2602.08171

Tran, Nguyen, Bashar, Ho, Nayak, Drovandi: Fast Model Selection and Stable Optimization for Softmax-Gated Multinomial-Logistic Mixture of Experts Models https://arxiv.org/abs/2602.07997 https://arxiv.org/pdf/2602.07997 https://arxiv.org/html/2602.07997

Kim, Parmar, Wallis, Miculicich, Jung, Dvijotham, Le, Pfister: CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution https://arxiv.org/abs/2602.07918 https://arxiv.org/pdf/2602.07918 https://arxiv.org/html/2602.07918

Huiyang Yi, Xiaojian Shen, Yonggang Wu, Duxin Chen, He Wang, Wenwu Yu: CausalCompass: Evaluating the Robustness of Time-Series Causal Discovery in Misspecified Scenarios https://arxiv.org/abs/2602.07915 https://arxiv.org/pdf/2602.07915 https://arxiv.org/html/2602.07915

Yufei Zhang, Zhihao Ma: Digital exclusion among middle-aged and older adults in China: age-period-cohort evidence from three national surveys, 2011-2022 https://arxiv.org/abs/2602.07785 https://arxiv.org/pdf/2602.07785 https://arxiv.org/html/2602.07785

Ruizhe Deng, Bibhas Chakraborty, Ran Chen, Yan Shuo Tan: BFTS: Thompson Sampling with Bayesian Additive Regression Trees https://arxiv.org/abs/2602.07767 https://arxiv.org/pdf/2602.07767 https://arxiv.org/html/2602.07767

Trevor Harris: Flow-Based Conformal Predictive Distributions https://arxiv.org/abs/2602.07633 https://arxiv.org/pdf/2602.07633 https://arxiv.org/html/2602.07633

Wanru Guo, Juan Xie, Binbin Wang, Weicong Chen, Xiaoyi Lu, Vipin Chaudhary, Curtis Tatsuoka: Robust Ultra-High-Dimensional Variable Selection With Correlated Structure Using Group Testing https://arxiv.org/abs/2602.07258 https://arxiv.org/pdf/2602.07258 https://arxiv.org/html/2602.07258

Matthew LeDuc, Tomoko Matsuo: PoissonRatioUQ: An R package for band ratio uncertainty quantification https://arxiv.org/abs/2602.07165 https://arxiv.org/pdf/2602.07165 https://arxiv.org/html/2602.07165

Rishikesh Yadav, Arnab Hazra: Regression modeling of multivariate precipitation extremes under regular variation https://arxiv.org/abs/2602.08865 https://arxiv.org/pdf/2602.08865 https://arxiv.org/html/2602.08865

Yuta Kawakami, Jin Tian: Measures for Assessing Causal Effect Heterogeneity Unexplained by Covariates https://arxiv.org/abs/2602.08647 https://arxiv.org/pdf/2602.08647 https://arxiv.org/html/2602.08647

Max Rubinstein, Megan S. Schuler, Elizabeth A. Stuart, Bradley D. Stein, Max Griswold, Elizabeth M. Stone, Beth Ann Griffin: State policy heterogeneity analyses: considerations and proposals https://arxiv.org/abs/2602.08643 https://arxiv.org/pdf/2602.08643 https://arxiv.org/html/2602.08643

Luca Presicce, Sudipto Banerjee: Adaptive Markovian Spatiotemporal Transfer Learning in Multivariate Bayesian Modeling https://arxiv.org/abs/2602.08544 https://arxiv.org/pdf/2602.08544 https://arxiv.org/html/2602.08544

Xiang Ye, Janet Van Niekerk, Haavard Rue: A Bayesian regression framework for circular models with INLA https://arxiv.org/abs/2602.08413 https://arxiv.org/pdf/2602.08413 https://arxiv.org/html/2602.08413

Takato Hashino, Koji Tsukuda: Estimating the Shannon Entropy Using the Pitman--Yor Process https://arxiv.org/abs/2602.08347 https://arxiv.org/pdf/2602.08347 https://arxiv.org/html/2602.08347

Jacob Tennenbaum, Adam Kapelner: Improved Conditional Logistic Regression using Information in Concordant Pairs with Software https://arxiv.org/abs/2602.08212 https://arxiv.org/pdf/2602.08212 https://arxiv.org/html/2602.08212

Juan Carlos Escanciano, Jacobo de U\~na-\'Alvarez: Goodness-of-Fit Tests for Censored and Truncated Data: Maximum Mean Discrepancy Over Regular Functionals https://arxiv.org/abs/2602.08108 https://arxiv.org/pdf/2602.08108 https://arxiv.org/html/2602.08108

Brian M Cho, Raaz Dwivedi, Nathan Kallus: GAAVI: Global Asymptotic Anytime Valid Inference for the Conditional Mean Function https://arxiv.org/abs/2602.08096 https://arxiv.org/pdf/2602.08096 https://arxiv.org/html/2602.08096

John W. Jackson, Ting-Hsuan Chang, Aster Meche, Trang Q. Nguyen: Estimation Strategies for Causal Decomposition Analysis with Allowability Specifications https://arxiv.org/abs/2602.07825 https://arxiv.org/pdf/2602.07825 https://arxiv.org/html/2602.07825

Buddhananda Banerjee, Surojit Biswas, Daitari Prusty: Hyperbolic statistical inference for Treatment Effects with Circular biomarker of astigmatism https://arxiv.org/abs/2602.07740 https://arxiv.org/pdf/2602.07740 https://arxiv.org/html/2602.07740

Chak Kwong (Tommy), Cheng, Hakan Demirtas: Generation of Multivariate Discrete Data with Generalized Poisson, Negative Binomial and Binomial Marginal Distributions https://arxiv.org/abs/2602.07707 https://arxiv.org/pdf/2602.07707 https://arxiv.org/html/2602.07707

Luk\'a\v{s} Laff\'ers, Jozef Michal Mintal, Ivan Sut\'oris: Correcting for Nonignorable Nonresponse Bias in Ordinal Observational Survey Data https://arxiv.org/abs/2602.07704 https://arxiv.org/pdf/2602.07704 https://arxiv.org/html/2602.07704

Qishi Zhan, Cheng-Han Yu, Yuchi Chen, Zhikang Dong, Rajarshi Guhaniyogi: Mapping Drivers of Greenness: Spatial Variable Selection for MODIS Vegetation Indices https://arxiv.org/abs/2602.07681 https://arxiv.org/pdf/2602.07681 https://arxiv.org/html/2602.07681

Jiuyao Lu, Tianruo Zhang, Ke Zhu: Fast Rerandomization for Balancing Covariates in Randomized Experiments: A Metropolis-Hastings Framework https://arxiv.org/abs/2602.07613 https://arxiv.org/pdf/2602.07613 https://arxiv.org/html/2602.07613

Jingwen Zhang, Satoshi Hattori: Event-driven type design for clinical trials with recurrent events https://arxiv.org/abs/2602.07482 https://arxiv.org/pdf/2602.07482 https://arxiv.org/html/2602.07482

Lena Schemet, Sarah Friedrich-Welz: Statistical inference after variable selection in Cox models: A simulation study https://arxiv.org/abs/2602.07477 https://arxiv.org/pdf/2602.07477 https://arxiv.org/html/2602.07477