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1584 papers in stat.ME · page 5
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Variance modeling stabilizes Michaelis-Menten estimates
Variance-Aware Estimation and Inference for Michaelis--Menten Models with Heteroscedastic Errors and Clustered Measurements
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Pre-trained net selects kernels for high-dim density estimates
Adaptive Kernel Density Estimation with Pre-training
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Reference pool of failures controls AI release errors on hard tasks
When Should an AI Workflow Release? Always-Valid Inference for Black-Box Generate-Verify Systems
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Bayesian model represents brain networks as mixtures of latent templates
A Bayesian Adaptive Latent Mixture Model for Zero-Inflated Weighted Brain Connectome Analysis
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The paper develops a penalized optimization method that jointly detects change points and…
Change-point detection in variance-covariance matrix
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IV estimand equals new DATE under stochastic potential outcomes
Never Too LATE: A Fully Stochastic Update to the Potential Outcome Framework
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Pairwise fusion penalty groups non-adjacent regions by COPD-income links
Linking COPD Prevalence with Income Distribution: A Spatial Heterogeneous Compositional Regression via Geographically Weighted Penalized Approach
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Fusion penalty groups non-adjacent regions by income-COPD links
Linking COPD Prevalence with Income Distribution: A Spatial Heterogeneous Compositional Regression via Geographically Weighted Penalized Approach
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Outcome delays inflate sample sizes in re-estimation trials
Evaluating the impact of outcome delay on the efficiency of sample size re-estimation
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Bias from thresholding predicted by residual score variance
When to Trust Confidence Thresholding: Calibration Diagnostics for Pseudo-Labelled Regression
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Longer blocks reduce efficiency in block maxima models
How long should a block be?
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ABC and Gini scores risk dishonest model rankings for point predictions
Measures of predictive accuracy, miscalibration and discrimination
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Surrogates estimate time-dependent failure probabilities efficiently
Time-variant reliability using time-dependent surrogate models
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Mixed-frequency synthetic controls reach optimal prediction error
Synthetic Control Method with Mixed Frequency Data
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Prior evidence boosts power in sequential multiple testing
Informative Simultaneous Confidence Intervals for Graphical Group Sequential Test Procedures
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Bayesian model links realized volatility to prices for better forecasts
Bayesian Dynamic Modeling of Realized Volatility in Financial Asset Price Forecasting
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Laplacian-P-splines yield fast Gamma frailty fits for clustered survival
Laplacian-P-splines for shared Gamma frailty models applied to clustered right-censored time-to-event data
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No single test dominates power across multivariate problems
Power Studies For Two-Sample and Goodness-of-Fit Methods For Multivariate Data
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Bayesian mixture clusters mixed health outcomes with low-rank regressions
Bayesian low-rank latent-cluster regression for mixed health outcomes
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Counterfactual probability identifies root causes from data
Probability of Root Cause: A Counterfactual Definition and Its Identification
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Nontargeted HPV infections isolate vaccine direct immune effect
Using NonTargeted HPV Infections in Studies with Risk Compensation
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Local clr LIMA detects composition mark clusters better than global averages
Uncovering Local Heterogeneity: Local Summary Characteristics for Spatial Point Processes with Composition-Valued Marks
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Unified theory supplies non-asymptotic bounds on conditional conformal errors
A Unified Theory of Conditional Coverage in Conformal Prediction with Applications
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Model-matched designs raise accuracy in plant selection trials
The design of selection experiments using a model-based approach
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Graph independences sharpen causal effect bounds
Exploiting independence constraints for efficient estimation of bounds on causal effects in the presence of unmeasured confounding
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Copula fixes dependence parameter to identify ordinal causal effects
Causal inference with ordinal outcomes: copula-based identification, estimation and sensitivity analysis
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Adapter adds closed-form spatial covariance to frozen predictors
Spatial Adapter: Structured Spatial Decomposition and Closed-Form Covariance for Frozen Predictors
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Inferring temperature improves hyperbolic models of tree-like networks
Hyperbolic Latent Space Models for Network Embedding: Model Specification and Bayesian Inference
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One operator unifies all regression types via measure choice
Unified Operator Framework for Functional and Multivariate Regression
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Similarity subgroups unmask hidden performance gaps in external validation
Rethinking external validation for the target population: Capturing patient-level similarity with a generative model
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Predictive resampling yields exact Bayesian posteriors
Variational predictive resampling
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VPR with mean-field predictives matches exact posteriors
Variational predictive resampling
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Noise-to-signal ratio acts as temperature in RG-based anomaly detection
Field Theory of Data: Anomaly Detection via the Functional Renormalization Group. The 2D Ising Model as a Benchmark
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FRG treats noise-to-signal ratio as temperature for anomaly detection
Field Theory of Data: Anomaly Detection via the Functional Renormalization Group. The 2D Ising Model as a Benchmark
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Indirect comparisons gain reliability when methods fit evidence strength
Indirect Comparisons For Health Technology Assessment: A Practical Methodological Guide And Tips With Insights From The French Transparency Commission
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Quantiles of AR errors recovered from observed series
Estimation of the Risk Measure under a Nuisance Autoregression
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This paper introduces two new stability measures for Bayesian decisions under prior…
Robust Bayes Acts under Prior Perturbations: Contamination, Stability, and Selection Paths
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Covariate-dependent level links low-fidelity quantiles to high-fidelity ones
Multi-Fidelity Quantile Regression
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Expert losses cut MoE training time for time series
Fast Training of Mixture-of-Experts for Time Series Forecasting via Expert Loss Integration
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Drop factor loadings below 0.70 in measurement models
Rethinking Factor Loading Thresholds: A Case for a Strict {\lambda} >= .70 Rule
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LDDMM distances enable Bayesian calibration of infinite-dimensional models
Diffeomorphic registration distances for Bayesian calibration of infinite-dimensional computer models
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Gaussian priors hit minimax rates for point-process intensity
Increasing domain asymptotics for covariate-based nonparametric Bayesian intensity estimation with Gaussian and Besov-Laplace priors
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New sample size formula for causal survival analysis uses few inputs
Sample size and power calculations for causal inference with time-to-event outcomes
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New formula gives sample sizes for causal survival studies
Sample size and power calculations for causal inference with time-to-event outcomes
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Past selections guide future choices via monotonicity model
A Statistical Framework for Learning Preferences from the Past
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Domino framework controls k-bFDR under any dependence
Generalized Boundary FDR Control under Arbitrary Dependence: An Approach on Closure Principle
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MCMC reaches O(ε²) error for time-changed SDE parameters at O(ε^{-2} log²ε) cost
Parameter Estimation for Partially Observed Time-Changed SDEs
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Proxy spectral structure identifies causal effects with hidden outcomes
Proximal Causal Inference for Hidden Outcomes
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GenusSink makes Sinkhorn near-linear on planar graphs
Near-Linear Time Generalized Sinkhorn Algorithms for Bounded Genus Graphs
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Near-linear Sinkhorn for geodesic transport on bounded-genus graphs
Near-Linear Time Generalized Sinkhorn Algorithms for Bounded Genus Graphs