arXiv Statistics @arxiv_stats@qoto.org

Optimal estimators for threshold-based quality measures https://arxiv.org/abs/2507.08811 #math.ST #math.PR #stat.TH

Mapping Dengue Vulnerability in Recife, Brazil: Socioeconomic Insights from PCA and Robust Regression https://arxiv.org/abs/2507.08814 #q-bio.PE #stat.AP

Predictive Causal Inference via Spatio-Temporal Modeling and Penalized Empirical Likelihood https://arxiv.org/abs/2507.08896 #stat.ME #stat.ML #cs.LG

Physics-informed machine learning: A mathematical framework with applications to time series forecasting https://arxiv.org/abs/2507.08906 #stat.ML #math.ST #stat.ME #stat.TH #cs.LG

Are Betting Markets Better than Polling in Predicting Political Elections? https://arxiv.org/abs/2507.08921 #stat.OT

The Bayesian Approach to Continual Learning: An Overview https://arxiv.org/abs/2507.08922 #stat.ML #cs.LG

Fixed-Confidence Multiple Change Point Identification under Bandit Feedback https://arxiv.org/abs/2507.08994 #stat.ML #cs.LG

Possibilistic inferential models: a review https://arxiv.org/abs/2507.09007 #math.ST #math.PR #stat.ME #stat.OT #stat.TH

Modeling Latent Underdispersion with Discrete Order Statistics https://arxiv.org/abs/2507.09032 #stat.ME

Hierarchical Bayesian Modeling of Total Column Ozone: Unraveling Equatorial Variability over Ethiopia Using Satellite Data and Multisource Covariates https://arxiv.org/abs/2507.09046 #stat.AP

Simultaneous Estimation and Model Choice for Big Discrete Time-to-Event Data with Additive Predictors https://arxiv.org/abs/2507.08099 #stat.ME

Mallows Model with Learned Distance Metrics: Sampling and Maximum Likelihood Estimation https://arxiv.org/abs/2507.08108 #stat.ML #math.PR #math.ST #stat.TH #cs.DS #cs.LG

Uncertainty quantification of a multi-component Hall thruster model at varying facility pressures https://arxiv.org/abs/2507.08113 #physics.plasm-ph #physics.comp-ph #stat.AP #stat.ML

Block Designs that Provide Optimal Power in the Cochran-Mantel-Haenszel Test https://arxiv.org/abs/2507.08125 #stat.ME

CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk https://arxiv.org/abs/2507.08150 #stat.ML #stat.ME #cs.LG

Optimal Experimental Design for Microplastics Sampling Experiments https://arxiv.org/abs/2507.08170 #stat.AP #stat.ME

Admissibility of Stein Shrinkage for Batch Normalization in the Presence of Adversarial Attacks https://arxiv.org/abs/2507.08261 #stat.ML #cs.LG

MIRRAMS: Towards Training Models Robust to Missingness Distribution Shifts https://arxiv.org/abs/2507.08280 #stat.ML #cs.LG

Testen statistischer Funktionale f\"ur Zweistichprobenprobleme https://arxiv.org/abs/2507.08373 #math.ST #stat.TH

A proposal for homoscedastic modelling with conditional auto-regressive distributions https://arxiv.org/abs/2507.08376 #stat.ME