archive
Every paper Pith has read. Search by title, abstract, or pith.
1584 papers in stat.ME · page 2
-
Nonparametric Bayesian statistics has grown since 1973
Topics in Nonparametric Bayesian Statistics
-
P-values from interpoint distance tests select cluster count
Evaluation of the number of clusters in a data set using $p$-values from Multiple Tests of Hypotheses
-
LLM interventions create user drift that biases simulated experiments
The Illusion of Intervention: Your LLM-Simulated Experiment is an Observational Study
-
Conformal tests bound false discoveries for every possible threshold
Everywhere Valid Bounds on False Discovery Proportions in Conformal Inference
-
New method checks observational CATE predictions against trial results
Assessing Estimate of CATE from Observational Data via an RCT Study
-
Joint model infers infectiousness from PCR data alone
Inferring infectiousness: a joint model of the within-host viral kinetics of SARS-CoV-2
-
Scale calibration makes median-of-means work for distributed PCA
Scale-Calibrated Median-of-Means for Robust Distributed Principal Component Analysis
-
Smoothing with auxiliary sample gives regression confidence regions
New Confidence Regions for Linear Regression Parameters with Stationary-Ergodic Dependent Errors
-
AIPW stays stable when propensity models are wrong
Application of Propensity Score Models and Causal Estimators in Observational Studies under Model Misspecification
-
New model detects category shifts in periodic time series
Changepoint Detection in Categorical Time Series with Application to Daily Total Cloud Cover in Canada
-
Imputation recovers causal effects from censored mediators
Evaluating causal indirect effects when mediators are left-censored by assay limit of quantification
-
New depth ranks sparse functional data without reconstruction
Conditional regularized halfspace depth for sparse functional data and its applications
-
Empirical Bayes reuses data twice and misses true posterior uncertainty
An Old Look at Empirical Bayes
-
Interval-length sampling minimizes worst-case error for bounded totals
Minimax unbiased estimation for finite populations with bounded outcomes
-
Time-varying hazard ratios fix meta-analysis when proportional hazards fail
Meta-analysis and network meta-analysis of time-to-event outcomes with non-proportional hazards: a Bayesian time-varying hazard ratio approach
-
Overlapping nuclear norms recover subgroup low-rank geometry
Group-Aware Matrix Estimation and Latent Subspace Recovery
-
One parameter suffices to infer signals with unknown background
Compensator-Based Inference for Signal Detection Under Unknown Background
-
Classifier uncertainty narrows conformal intervals by 39% for confident cases
CASCADE Conformal Prediction: Uncertainty-Adaptive Prediction Intervals for Two-Stage Clinical Decision Support
-
Distance plots estimate Hurst exponents in multivariate long-memory processes
Pairwise Distance-Diffusion Analysis (PDDA): A Geometric Framework for Estimating Hurst Exponents in Multivariate Long-Memory Processes
-
Harmonic Synthetic Control adapts to mixed stochastic trends
The Harmonic Synthetic Control Method
-
Separable covariance links functional data to matrix distributions
Explainable Outlier Detection for Multivariate Functional Data
-
Imputing DAH components keeps type I error stable
Component over Composite: Mitigating Type I Error Inflation when Imputing "Days Alive and at Home"
-
Component imputation prevents type I error inflation in DAH trials
Component over Composite: Mitigating Type I Error Inflation when Imputing "Days Alive and at Home"
-
Post-hoc calibration sharpens GP lower tails for optimization
Goal-Oriented Lower-Tail Calibration of Gaussian Processes for Bayesian Optimization
-
Ratio of tail mean to quantile captures upper-tail persistence
Quantile-Based Effectiveness Persistence Function: A Tail-Focused Metric with Theory, Estimation, and Application to Biosimilar Evaluation
-
Complete-case beats weighting in federated missing-data studies
Federated Learning with Incomplete Data: When to Use Complete Cases and When to Weight
-
Goodness-of-fit test for IC models works without pre-whitening
A Goodness-of-Fit Test for Independent Component Models in High Dimensions
-
Extended bridge functions recover joint interventional distributions with all proxies
Identifying Interventional Joint Distributions via Extended Bridge Functions
-
Cloning-censoring-weighting estimates effects of 2 vs 5 years tamoxifen
Estimating treatment duration effects via clone-censor-weight: a breast cancer case study
-
Gated estimator cuts manifold density error by 22-36%
Variance-Reduced Manifold Sampling via Polynomial-Maximization Density Estimation
-
Tolerance limits work under selection bias and censoring
Sample Size Determination Under Selection Bias: Robust Tolerance Limits for Prevalent Cohort Data
-
Spatial statistics unmix stationary from nonstationary signals
Stationary subspace analysis for spatial data
-
Adaptive sampling yields reliable model selection under non-identifiability
Reliable model selection in the presence of parameter non-identifiability
-
Variance mismatch, not small size, inflates errors in risk difference tests
Assessing covariate-adjusted risk differences in small-sample clinical trials
-
Treatment effect on survival splits into four mechanisms via competing events
Causal treatment effect decompositions with time-to-event outcomes under competing events
-
Divergence measures locate where tree surrogates lose fidelity
A Family of Divergence Measures for Evaluating the Reconstruction Quality of Explainable Ensemble Trees
-
Variational EM estimates ideal points and errors faster than MCMC
Uncertainty-Aware Ideal Point Estimation via Variational EM
-
Fréchet regression gains tests for predictor effects
Inference for Fr\'echet Regression
-
Method clusters subjects and learns their distinct causal graphs
A Unified Framework for Structure-Aware Clustering and Heterogeneous Causal Graph Learning
-
Probabilistic model equips rankings with confidence intervals
Ranking with Confidence: A Probabilistic Framework for Deterministic Ranking Methods
-
Inference functionals give consistency for models without densities
Inference Functionals and Observation Operators for Distributional Statistical Models
-
Spatial Cramér-von Mises test extended to β-mixing fields
The Spatial Cram'{e}r--von Mises Test of Independence under $\beta$-Mixing: Asymptotic Theory and Python Implementation
-
Posterior means raise clinical utility over plug-in predictions
Progression to the mean: A comparison of Bayesian clinical prediction models outputting the posterior mean versus conventional plug-in predictions
-
Greedy method learns optimal integer clinical risk scores directly
Learning Interpretable Point-Based Clinical Risk Scores via Direct Optimization
-
R package models marked point processes with location-dependent marks
ldmppr: Location Dependent Marked Point Processes in R
-
Refinement recovers sparse response patterns in latent class models
Sparse Latent Class Analysis: Post-Estimation Refinement via Item-level Pseudo-Likelihood
-
Beta law tracks conformal coverage under dependence
Conformal Prediction via Transported Beta Laws
-
Categorical confounder makes causal effects identifiable from proxies or multiple tests
Causal Inference with Categorical Unobserved Confounder via Mixture Learning
-
-
Bridge score yields sharp bounds on mediator-outcome confounding
Sensitivity analysis for causal mediation: bridge score, sharp sensitivity bounds, and calibration