arXiv Statistics @arxiv_stats@qoto.org

Right-censored models on massive data https://arxiv.org/abs/2502.00178 #math.ST #stat.TH

PRECISE: PRivacy-loss-Efficient and Consistent Inference based on poSterior quantilEs https://arxiv.org/abs/2502.00192 #stat.ME

Score-Preserving Targeted Maximum Likelihood Estimation https://arxiv.org/abs/2502.00200 #stat.ME #math.ST #stat.TH

Proportional effect models for continuous outcomes are biased https://arxiv.org/abs/2502.00214 #stat.ME

A simple multistage theory for multimorbidity https://arxiv.org/abs/2501.18742 #q-bio.QM #stat.ME

A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization https://arxiv.org/abs/2501.18756 #stat.ML #math.OC #cs.LG

Low-Rank Approaches to Graphon Learning in Networks https://arxiv.org/abs/2501.18785 #stat.ME

Targeted Data Fusion for Causal Survival Analysis Under Distribution Shift https://arxiv.org/abs/2501.18798 #stat.ME

Recent advances in doubly-robust weighted ordinary least squares techniques for dynamic treatment regime estimation https://arxiv.org/abs/2501.18819 #stat.ME

Bayesian mixture modeling using a mixture of finite mixtures with normalized inverse Gaussian weights https://arxiv.org/abs/2501.18854 #stat.ME

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models https://arxiv.org/abs/2501.18863 #stat.ML #cs.LG

Measuring Inaccuracies in the Proportional Hazard Rate Model based on Extropy using a Length-Biased Weighted Residual approach https://arxiv.org/abs/2501.18888 #stat.ME

Trustworthy Evaluation of Generative AI Models https://arxiv.org/abs/2501.18897 #stat.ML #cs.LG

Analyzing Classroom Interaction Data Using Prompt Engineering and Network Analysis https://arxiv.org/abs/2501.18912 #stat.AP #cs.SI

Normalizing Flows for Gaussian Process Regression under Hierarchical Shrinkage Priors https://arxiv.org/abs/2501.13173 #stat.ME

Sequential One-Sided Hypothesis Testing of Markov Chains https://arxiv.org/abs/2501.13187 #stat.AP #math.ST #stat.TH

Design of Bayesian Clinical Trials with Clustered Data and Multiple Endpoints https://arxiv.org/abs/2501.13218 #stat.ME

Peak Inference for Gaussian Random Fields on a Lattice https://arxiv.org/abs/2501.13239 #stat.ME

A Bayesian Record Linkage Approach to Applications in Tree Demography Using Overlapping LiDAR Scans https://arxiv.org/abs/2501.13285 #stat.ME #stat.AP

Enterprise Experimentation with Hierarchical Entities https://arxiv.org/abs/2501.13293 #stat.ME