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
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
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
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
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