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1584 papers in stat.ME · page 17
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AAA ratings for structured credit needed 10,000:1 discrimination
When AAA Satisfies Nothing: Impossibility Theorems for Structured Credit Ratings
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Precision matrix gives Gaussian processes partial correlation networks
Partial correlation networks of Gaussian processes
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No single method leads in rare-outcome EHR phenotyping simulations
Performance of weakly-supervised electronic health record-based phenotyping methods in rare-outcome settings
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Mixed membership extends to multilevel functional data
Mixed Membership Models for Multilevel Functional Data
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Crumble enables mediation analysis despite intermediate confounding
crumble: A comprehensive framework for modern causal mediation analysis with intermediate confounding
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Coupling designs boost efficiency in complex treatment experiments
Coupling Designs for Randomized Experiments with Complex Treatments
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Conditioning on selection restores valid inference after data-driven choices
Inference conditional on selection: a review
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Manifold regression recovers topology at optimal rate
Harmonic Map Regression: Rate-Optimal Nonparametric Estimation on Manifolds with Topological Recovery
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Drop-the-loser design with early superiority stopping cuts expected sample size
A Multi-Stage Drop-the-Loser Design with Superiority Boundaries
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Maximum-of-differences test compares K multivariate distributions
Maximum-of-Differences Test for Comparing Multivariate K-Sample Distributions
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Bayesian variance guides optimal step-stress designs with competing risks
Exact Bayesian Planning for Simple Step-Stress Accelerated Life Testing with Competing Risks
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Bonferroni keeps most power in A/B tests when limited to success metrics
Nobody Puts Bonferroni in a Corner
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Score-driven updates extend Elo to any probabilistic game outcome
Score-Driven Rating System for Sports
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Single known proxy identifies causal effects under completeness
Identifying Causal Effects Using a Single Proxy Variable
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Non-significant p-values hide three different trial outcomes
A Practical Guide to Interpret a Randomized Controlled Trial
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Tighter bounds on false discoveries for heterogeneous data
Confidence envelopes for the false discoveries with heterogeneous data
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Inferential models give exact coverage for constrained parameters
Constructing confidence intervals for constrained parameters via valid prior-free inferential models
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Bayesian method fits local DLNMs to sparse count data efficiently
Spatially varying distributed lag non-linear models using Laplacian P-splines
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One functional recovers ATE or direct effect under role ambiguity
Model-Robust Direct Effect Under Confounder-Mediator Ambiguity
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Calibration studies unlock causal estimates from observational data
The Illusion of Learning from Observational Data: An Empirical Bayes Perspective
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Auctions procure data of unknown quality with honest seller reports
Buying Data of Unknown Quality: Fisher Information Procurement Auctions
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Low-rank tensor design scales factorial experiments with rank not size
Policy-Aware Design of Large-Scale Factorial Experiments
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Moment ratio identifies latent group effect from calibrated score
Identification of Latent Group Effects under Conditional Calibration
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Bridge functions recover comparable latent treatment effects
Nonparametric Identification and Estimation of Causal Effects on Latent Outcomes
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Python toolkit runs 10 tests to diagnose time series non-stationarity
StationarityToolkit: Comprehensive Time Series Stationarity Analysis in Python
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QuasiMed mediates single-cell data with only mean functions
A Quasi-Regression Method for the Mediation Analysis of Zero-Inflated Single-Cell Data
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Bayesian model selects covariates separately for each response coordinate
Bayesian Semiparametric Multivariate Density Regression with Coordinate-Wise Predictor Selection
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Individual variations yield realistic average effect size hypotheses
Hypothesizing an effect size by considering individual variation
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Semiparametric method cuts error in mediation analysis for non-normal data
Semiparametric Causal Mediation Analysis for Linear Models with Non-Gaussian Errors: Applications to Drug Treatment and Social Program Evaluation
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Choquet integral wins in 15 of 17 heart trial simulations
Multi-Dimensional Composite Endpoint Analysis via the Choquet Integral: Block Recurrent Encoding and Comparative Advantage Mapping
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Semiparametric elliptical mixtures deliver consistent clusters and efficient estimates
Unsupervised Learning Under a General Semiparametric Clusterwise Elliptical Distribution: Efficient Estimation, Optimal Clustering, and Consistent Cluster Selection
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Poisson nodes yield consistent spectra in dot-product graphs
Intensity Dot Product Graphs
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Cross-fitted TMLE reaches efficiency bound for ATE under parametric mean
Efficient Targeted Maximum Likelihood Estimation of Average Treatment Effects under Structured Outcome Models with Unknown Error Distributions
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Tensor model forecasts Alzheimer's brain changes from MRI
Bayesian Tensor-on-Tensor Varying Coefficient Model for Forecasting Alzheimer's Disease Progression
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Fixed-effects models stay consistent for cluster trial effects despite misspecification
Fixed-Effects Models for Causal Inference in Longitudinal Cluster Randomized and Quasi-Experimental Trials
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Log-Laplace nugget enables high-dimensional spatial extremes fitting
Log-Laplace Nuggets for Fully Bayesian Fitting of Spatial Extremes Models to Threshold Exceedances
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Sample split regression removes high-dimensional bias from surveys
Sample-split REGression SREG: A robust estimator for high-dimensional survey data
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IV sensitivity analysis yields linear-program bounds without monotonicity
Assessing Sensitivity to IV Exclusion and Exogeneity without First Stage Monotonicity
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Model splits label disagreements into four measurable sources
From Ground Truth to Measurement: A Statistical Framework for Human Labeling
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Gumbel MAGMAR copula best captures clustered sovereign rating changes
Climate-Aware Copula Models for Sovereign Rating Migration Risk
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Weighted quantile regression on ratio estimates yields Mendelian randomization results…
Robust Mendelian Randomization Estimation using Weighted Quantile Regression
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Covariance matrices vary with covariates via Cholesky
A covariate-dependent Cholesky decomposition for high-dimensional covariance regression
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Gradient Langevin method speeds balanced rerandomization
Langevin-Gradient Rerandomization
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LASSO on Cholesky factor sparsifies multivariate spatial covariances
Regularized estimation for highly multivariate spatial Gaussian random fields
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RMT framework extracts spatial patterns from climate time series
Eliciting core spatial association from spatial time series: a random matrix approach
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Virtual dummies enable FDR variable selection at million-predictor scales
Virtual Dummies: Enabling Scalable FDR-Controlled Variable Selection via Sequential Sampling of Null Features
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SCDR delivers asymptotic coverage for time series predictions
Conformal Prediction with Time-Series Data via Sequential Conformalized Density Regions
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Text priors improve Q-matrix recovery in dynamic cognitive models
NLP-Informed Dynamic Cognitive Diagnosis Modelling
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Normalized MMD receives explicit finite-sample quantile bound
Non-asymptotic two-sample kernel testing with the spectrally truncated normalized MMD
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Federation with privacy boosts high-dimensional time series accuracy
Private Federated Learning for High-dimensional Time Series