arXiv Statistics @arxiv_stats@qoto.org

Fast approximative estimation of conditional Shapley values when using a linear regression model or a polynomial regression model https://arxiv.org/abs/2504.18167 #stat.ME #stat.ML

Learning Operators by Regularized Stochastic Gradient Descent with Operator-valued Kernels https://arxiv.org/abs/2504.18184 #stat.ML #math.FA #math.ST #stat.TH #cs.LG

Auto-Regressive Standard Precipitation Index: A Bayesian Approach for Drought Characterization https://arxiv.org/abs/2504.18197 #stat.AP

A Weighted-likelihood framework for class imbalance in Bayesian prediction models https://arxiv.org/abs/2504.17013 #stat.AP #stat.ML

A Sensitivity Analysis Framework for Quantifying Confidence in Decisions in the Presence of Data Uncertainty https://arxiv.org/abs/2504.17043 #stat.ME #stat.AP

Conditional-Marginal Nonparametric Estimation for Stage Waiting Times from Multi-Stage Models under Dependent Right Censoring https://arxiv.org/abs/2504.17089 #stat.ME

MOOSE ProbML: Parallelized Probabilistic Machine Learning and Uncertainty Quantification for Computational Energy Applications https://arxiv.org/abs/2504.17101 #stat.AP

Target trial emulation without matching: a more efficient approach for evaluating vaccine effectiveness using observational data https://arxiv.org/abs/2504.17104 #stat.ME #stat.AP

Physics-informed features in supervised machine learning https://arxiv.org/abs/2504.17112 #stat.ML #math.NA #cs.LG #cs.NA

Estimation and Inference for the Average Treatment Effect in a Score-Explained Heterogeneous Treatment Effect Model https://arxiv.org/abs/2504.17126 #stat.ME #math.ST #stat.TH

A Delayed Acceptance Auxiliary Variable MCMC for Spatial Models with Intractable Likelihood Function https://arxiv.org/abs/2504.17147 #stat.ME #stat.CO

Causal rule ensemble approach for multi-arm data https://arxiv.org/abs/2504.17166 #stat.ML #cs.LG

A general approach to modeling environmental mixtures with multivariate outcomes https://arxiv.org/abs/2504.17195 #stat.ME

Parental Imprints On Birth Weight: A Data-Driven Model For Neonatal Prediction In Low Resource Prenatal Care https://arxiv.org/abs/2504.15290 #stat.OT

A New Multiple Correlation Coefficient without Specifying the Dependent Variable https://arxiv.org/abs/2504.15372 #stat.ME

Assessing Surrogate Heterogeneity in Real World Data Using Meta-Learners https://arxiv.org/abs/2504.15386 #stat.ME #stat.ML #cs.LG

Deep learning with missing data https://arxiv.org/abs/2504.15388 #stat.ME #math.ST #stat.ML #stat.TH #cs.LG

ORKM: An R Package for Online Multi-View Data https://arxiv.org/abs/2504.15402 #stat.AP #stat.CO

A stochastic method to estimate a zero-inflated two-part mixed model for human microbiome data https://arxiv.org/abs/2504.15411 #stat.ME #math.ST #stat.TH

Micro-randomized Trials with Categorical Treatments: Causal Effect Estimation and Sample Size Calculation https://arxiv.org/abs/2504.15484 #stat.ME