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1584 papers in stat.ME · page 15
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Berry-Esseen bound controls covariance error for long-range series
Simultaneous Inference for Covariance and Precision Matrices of Long-Range Dependent Time Series
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Bayesian windows from past trials stabilize crop variance estimates
A Bayesian Updating Framework for Long-term Multi-Environment Trial Data in Plant Breeding
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Model isolates intrinsic scores from context effects in rankings
Deep Ranking with Heterogeneous Effects
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Joint models recover transition parameters better than stepwise ones
A Comparison of Joint and Stepwise Dynamic Cognitive Diagnostic Models
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Phase transitions mark breakdown of statistical indistinguishability
Phase Transitions as the Breakdown of Statistical Indistinguishability
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Modified Greenwood statistic tests bivariate alpha-stable laws
Testing and estimation of the index of stability of univariate and bivariate symmetric $\alpha-$stable distributions via modified Greenwood statistic
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Workflows guide selection of process capability indices
Practical Process Capability Indices Workflows
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Financial ML backtests often detect nonexistent predictability
Spurious Predictability in Financial Machine Learning
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Mismatch between cohorts degrades prognostic model calibration
Robustifying and Selecting Cohort-Appropriate Prognostic Models under Distributional Shifts
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Augmented SVGD tracks posterior mode branching as priors change
Sample continuation in Bayesian hierarchical model via variational inference
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Block aggregation yields fine-scale inferences from coarse data
Spatially continuous modelling of aggregated outcome data
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Order statistic inequality holds approximately under mild violations
On a Probability Inequality for Order Statistics with Applications to Bootstrap, Conformal Prediction, and more
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Joint Bayesian model lowers error for mixed survey responses
A Bayesian Approach to Unit-level Dependent Multi-type Survey Data
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CRTB handles cellwise outliers in twoblock dimension reduction
Cellwise Robust Twoblock Dimension Reduction
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Adaptive weights on priors improve high-dimensional GLM models
Adaptive Multi-Prior Lasso for High-Dimensional Generalized Linear Models
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Ensemble member differences capture aleatoric uncertainty
Capturing Aleatoric Uncertainty in Climate Models
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Ranked choices cut conjoint standard errors by up to 55%
Ranked-choice conjoint experiments
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Weighted residuals restore valid tests for regressions with growing predictors
Model Checking for Regressions Based on Weighted Residual Processes with Diverging Number of Predictors
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Unified adaptive design merges screening and optimization
HASOD: A Hybrid Adaptive Screening-Optimization Design for High-Dimensional Industrial Experiments
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Orthogonal moments let AI data safely enhance human-label estimates
Generative Augmented Inference
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Bayesian method links PCoA axes to driving taxa
Bayesian sparse principal coordinates analysis with delta-tolerant linear approximation for microbiome data
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Bayesian model flags graph outliers with posterior probabilities
Bayesian Node-Level Outlier Detection for Graph Signals
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Stratify propensity weights by clinical subgroups for better balance
Propensity Score Weighting to Ensure Balance in Key Subgroups or Strata: A Practical Guide
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Early stopping yields optimal adaptive rates with less computation
Early-stopped aggregation: Adaptive inference with computational efficiency
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Capacity limits make accuracy-based thresholds suboptimal for AI interventions
Deployment of AI-Assisted Interventions: Capacity Constraints and Noisy Compliance
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Framework scores proxies for correct A/B launch decisions
PROXIMA: A Reliability Scoring Framework for Proxy Metrics in Online Controlled Experiments
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Hybrid inference yields lab-specific CNV guarantees
Combining Bayesian and Frequentist Inference for Laboratory-Specific Performance Guarantees in Copy Number Variation Detection
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Selective external control borrowing cuts ATE mean squared error
Improving Treatment Effect Estimation in Trials through Adaptive Borrowing of External Controls
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Sum and max statistics test alpha under dependence in high dimensions
Testing Alpha in High-Dimensional Conditional Time-Varying Factor Models with Dependent Observations
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Validation clusters improve time series forecasts without downside
Forecasting Multivariate Time Series under Predictive Heterogeneity: A Validation-Driven Clustering Framework
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R package finds sample sizes for any simulatable trial
Adaptive Sample Size Simulations with R package adsasi
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Fractional covariance works for infinite-variance cyclostationary series
Fractional lower-order covariance-based measures for cyclostationary time series with heavy-tailed distributions: application to dependence testing and model order identification
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Evidence-aware RL makes radiology reports more faithful
Enhancing Reinforcement Learning for Radiology Report Generation with Evidence-aware Rewards and Self-correcting Preference Learning
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Two-stage kernel ridge regression estimates continuous treatment effects
Estimating Continuous Treatment Effects with Two-Stage Kernel Ridge Regression
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ML framework estimates individual treatment effects in cluster trials
Leveraging machine learning to estimate individualized treatment effects in cluster-randomized trials
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Newton recursion is discrete Fisher-Rao gradient flow
Newton's Algorithm as a Gradient Flow: A Geometric Framework for Recursive Mixture Estimation
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Fixed centre effects control confounding in LAGO trials
Addressing Confounding by Indication Through (Un)Measured Centre Characteristics in Learn-As-you-GO(LAGO) Trials
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Fixed center effects remove unmeasured confounding in LAGO trials
Addressing Confounding by Indication Through (Un)Measured Centre Characteristics in Learn-As-you-GO(LAGO) Trials
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Fusing trial and immunobridging data estimates counterfactual vaccine incidence
Efficient estimation of cumulative incidence curves via data fusion with surrogates: application to integrated analysis of vaccine trial and immunobridging data
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Model estimates alerts at any time or dose using full dataset
Estimating effect thresholds and beyond: A flexible framework for multivariate alert detection
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BC-ACI trims interval scores 13-17% after mean shifts
Bias-Corrected Adaptive Conformal Inference for Multi-Horizon Time Series Forecasting
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Estimator achieves parametric rates for network quantile effects
Nonparametric efficient inference for network quantile causal effects under partial interference
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Martingale conditions identify causal effects in marked point processes
On causal inference with marked point process data
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Emulating stepped-wedge trials clarifies causal claims in staggered policy data
Emulating Stepped-Wedge Cluster Randomized Trials to Evaluate Health Policies and Interventions
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Causal proportion quantifies how much a longitudinal surrogate explains treatment effects
A Causal Framework for Evaluating Jointly Longitudinal Outcomes and Surrogate Markers: A State-Space Approach
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Model lets dependence among mixed outcomes vary with a covariate
Bayesian Nonparametric Modeling for Multivariate Conditional Copula Regression with Varying Coefficients
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This paper proves that sharp analytical bounds on the average treatment effect in…
Fundamental Limits and Optimal Methods for Sharp Analytical Causal Bounds in Instrumental Variable Models