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Every paper Pith has read. Search by title, abstract, or pith.
1584 papers in stat.ME · page 7
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K-means finds stable clusters in continuous data with no groups
Drawing Lines in Psychological Space: What K-means Clustering Reveals in Simulated and Real Psychometric Data
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Shared calibration reverses LLM judge comparisons
Bias and Uncertainty in LLM-as-a-Judge Estimation
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Multi-stage smoothing recovers evolving network edges
Nonparametric estimation of time-varying network connections by multi-stage smoothing
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Small capability errors amplify into large defect risks
Nonlinear Amplification of Finite-Sample Uncertainty in Capability-Based Decisions
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Bayesian model contracts to true dynamic correlations at explicit rate
Modeling Dynamic Correlation Matrices with Shrinkage Priors
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Variance estimator fixes type I error for rare binary trial outcomes
Improving Variance Estimation for Covariate Adjustment with Binary Outcomes
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Adaptive covariate selection preserves RCT validity under budget limits
DARTS: Targeting Prognostic Covariates in Budget-Constrained Sequential Experiments
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One estimator formula covers many adaptive subpopulation selection rules
Unbiased estimation in two-stage adaptive enrichment designs
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History-aware sets shorten survival predictions while keeping coverage
History-Aware Conformal Prediction Sets for Censored Time-to-Event Outcomes
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Sequential trials with subsidies raise social utility over 35%
Optimizing Social Utility in Sequential Experiments
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Jeffreys Bayes estimator beats MLE on small Frank copula samples
Bivariate Frank Copula: Some More Results on Point Estimation of the Association Parameter from a Bayesian Perspective and Revisiting the Goodness of Fit Tests with an Application to Model Groundwater Data from Dong Thap, Vietnam
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Proxy inferences calibrated by random effects from past domains
Estimate Level Adjustment For Inference With Proxies Under Random Distribution Shifts
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Statistical bounds quantify success for multiple groups steering one classifier
A Statistical Framework for Algorithmic Collective Action with Multiple Collectives
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Neyman score dictates balancing in debiased machine learning
Covariate Balancing and Riesz Regression Should Be Guided by the Neyman Orthogonal Score in Debiased Machine Learning
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Bayesian tensor model estimates multi-feature contact matrices
Bayesian Modeling and Prediction of Generalized Contact Matrices
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Sorting by relatives recovers causal order in random DAGs
A Topological Sorting Criterion for Random Causal Directed Acyclic Graphs
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Bayesian averaging of fractional polynomials recovers optimal doses
Bayesian Fractional Polynomials for Optimal Dosage Estimation with Fish Nutrition Applications
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Two-level model improves route predictions for mobility apps
A Two-Level Plackett-Luce Model for preference modeling in smart mobility platforms
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Direct volume minimization gives conditional quantiles
Super-Level-Set Regression: Conditional Quantiles via Volume Minimization
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Linked tensor model shows varying fluoride effects on paired tooth diseases
Linked-Tucker Factorized Individualized Regression for Paired Multivariate Categorical Outcomes
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Linked Tucker model ties fluoride to fluorosis and soda to caries
Linked-Tucker Factorized Individualized Regression for Paired Multivariate Categorical Outcomes
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TabCF turns tabular models into fast control function estimators
TabCF: Distributional Control Function Estimation with Tabular Foundation Models
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Framework separates effects in bundled versus independent treatment designs
Separable Effects in Four-Arm and Two-Arm Designs
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Sequential design gives consistent estimates from non-probability samples
Toward design-based inference for data integration
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Two-step method adds biomarker variability to joint survival models
Joint modelling of time-dependent biomarker variability and time-to-event outcomes, a two-step approach
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Balanced representations let flow matching recover causal outcome distributions
RepFlow: Representation Enhanced Flow Matching for Causal Effect Estimation
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CITE certifies target answers as LLM response modes with anytime-valid guarantees
CITE: Anytime-Valid Statistical Inference in LLM Self-Consistency
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Stochastic interventions balance meds to isolate treatment effects
Estimation of treatment effects in presence of differential use of post-randomization concomitant medication with time-to-event outcomes
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Method finds optimizers for conditional stochastic problems
Unbiased Gradients for a Class of Conditional Stochastic Optimization Problems
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Kernel copula embeddings detect causal dependence shifts
Detecting Changes in Causal Dependence with Kernels and Copulas
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Dual-homotopy keeps EM monotonic under any constraints
Dual-Homotopy Framework for Constrained EM Algorithm
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Dual-homotopy framework keeps constrained EM likelihoods strictly increasing
Dual-Homotopy Framework for Constrained EM Algorithm
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Matched low-discrepancy subsample enables valid DML at sqrt(r) scale
UD-DML: Uniform Design Subsampling for Double Machine Learning over Massive Data
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Generative AI creates realistic data for better Monte Carlo method tests
Generative AI-Based Monte Carlo Simulation for Method Evaluation Using Synthetic Multilevel Data
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Stein characterization yields omnibus test for discrete Pareto
A Stein Characterization-type Omnibus Tests for the Discrete Pareto Distribution
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l1-regularized model detects hidden groups and biased test items
Latent Impact and Differential Item Functioning Analysis for Asymmetric IRT Models
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Causal estimate trims BP benefit on heart disease to 3.4%
Causal Inference of Blood Pressure Reduction and Coronary Heart Disease Risk in the Framingham Study
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Transversality makes statistical degeneracies non-generic
Notes on Transversality and Statistical Degeneracies in Distributional Models
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Marginal conformal coverage leaves 13-point subgroup gaps in survey data
Socio-Conformal Calibration in Complex Survey Data: Marginal Validity Is Not Enough for Subgroup Reliability
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Metaverse framework proposed for immersive statistical education
Welcome to the Statverse: A Metaverse for Data Science
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Direct sampling replaces Metropolis for global scale in sparse regression
Spectral Collapsed Gibbs Sampler for Bayesian Sparse Regression
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RG analysis yields lattice design rules and regularization scaling for GLMs
A renormalization-group inspired lattice-based framework for piecewise generalized linear models
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Method recovers active predictors and their simple or complex forms
Model Form Identification in High-Dimensional Functional Linear Regressions
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Latent temperature fluctuation enables EM for kappa fits
Parameter estimation for kappa distributions using the EM algorithm in the superstatistical framework
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Latent gamma temperature gives EM closed forms for kappa fits
Parameter estimation for kappa distributions using the EM algorithm in the superstatistical framework
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Latent gamma temperature yields closed-form EM for kappa fits
Parameter estimation for kappa distributions using the EM algorithm in the superstatistical framework
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Template matching yields causal RMST estimates in case-cohort studies
Causal Effect Estimation on Restricted Mean Survival Time in Case-Cohort Studies via a Matching Design
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Shrinkage prior with spatial links selects clustered predictors in Poisson models
Bayesian Region Selection and Prediction in Poisson Regression with Spatially Dependent Global-Local Shrinkage Prior
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BISG sampling matches Pew Jewish survey at fraction of cost
Improving Minority Population Sampling with BISG Probabilities: Evidence from a Survey of Jewish Americans
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Multilevel model projects covariances to sphere for cluster-wise regression
Multilevel Regression Modeling of Covariance Matrix Outcomes