archive
Every paper Pith has read. Search by title, abstract, or pith.
1584 papers in stat.ME · page 16
-
Bayes factor sets variable inclusion and stops iterations early
A Bayes-Factor-Guided Approach to Post-Double Selection with Bootstrapped Multiple Imputation
-
Graphical SLOPE error converges to convex SLOPE limit
Asymptotic Theory for Graphical SLOPE: Precision Estimation and Pattern Convergence
-
This paper compares three statistical frameworks for evaluating treatments using multiple…
Navigating the Landscape of Hierarchical Multi-Component Strategies: GPC, DOOR, and MOST
-
Spectral co-clustering tracks evolving communities in VAR processes
Latent community paths in VAR-type models via dynamic directed spectral co-clustering
-
Panel ES regression yields tail factors with distinct pricing info
Expected Shortfall Panel Regression
-
New bivariate model handles extremes at any threshold
A sub-asymptotic model for bivariate threshold exceedances
-
Small method combinations match top performers in 90-95% of cases
An Empirical Comparison of Methods for Quantifying the Similarity of Numeric Datasets
-
Fine-tuning beats single-task learning under sample size conditions
SMART Fine-tuning Factor Augmented Neural Lasso
-
Residual tuning yields optimal rates in high-dimensional fine-tuning
SMART Fine-tuning Factor Augmented Neural Lasso
-
Optimal transport yields sharp bounds on policy-relevant treatment effects
Partial Identification of Policy-Relevant Treatment Effects with Instrumental Variables via Optimal Transport
-
A spatial-sign max-type test for high-dimensional alpha is asymptotically independent…
Robust Spatial-Sign-Based Testing of High-Dimensional Alpha in Conditional Factor Models
-
Balancing inferred latent factor yields RCT-like survival estimates
Observing the unobserved confounding through its effects: toward randomized trial-like estimates from real-world survival data
-
Seven-parameter model estimates dependent stress-strength reliability
Reliability estimation in dependent stress-strength model with Clayton copula and modified Weibull margins
-
Point-process counts identified under spillover treatments
Causal inference for spatiotemporal point processes in the presence of outcome spillover and carryover
-
Exact variance enables valid limits from first sample in binary streams
A Nonparametric Adaptive EWMA Control Chart for Binary Monitoring of Multiple Stream Processes
-
-
A new SV-ADF test detects and dates bubble episodes under persistent volatility
Is There an AI Bubble? Robust Date-Stamping for Periods of Exuberance
-
ConvMMD performs inference on noisy data
Convolutional Maximum Mean Discrepancy for Inference in Noisy Data
-
Exact tests derived for Weibull survival under Type-I censoring
Inference on Survival Reliability with Type-I Censored Weibull data
-
Sample weights locate change points in high-dimensional regression
Inferring Change Points in Regression via Sample Weighting
-
Nested model clusters cells and donors by genotype and expression
Nested Atoms Model with Application to Clustering Big Population-Scale Single-Cell Data
-
NetworkNet estimates nodal expansiveness and popularity
NetworkNet: A Deep Neural Network Approach for Random Networks with Sparse Nodal Attributes and Complex Nodal Heterogeneity
-
One spectral decomposition replaces two per model for ICAR priors
A novel reference prior for Gaussian hierarchical models with intrinsic conditional autoregressive random effects
-
Local covariate neighborhoods enable inference in dense high-dim models
Principled Inference in Dense High-Dimensional Linear Models via Local Conditional Sparsity
-
ADD achieves 100% accurate 48-bit watermarks resilient to distortions
ADD for Multi-Bit Image Watermarking
-
Friedman-Rafsky test recommended for two categorical datasets
An Empirical Comparison of Methods for Quantifying the Similarity of Categorical Datasets
-
GLS regression standardises log-law fits without choosing the region
Generalised least squares approach for estimation of the log-law parameters of turbulent boundary layers
-
A new measure treats impact, novelty, and disruptiveness as strict complements in…
Which Discoveries Are Paradigm Shifting?
-
Nonparametric estimator tracks tail dependence in non-identical data
Trends in tail dependence of heteroscedastic extremes
-
Tensor factor models detect multiple change points and affected modes
Detection and Mode-Identification of Multiple Change Points in Tensor Factor Models
-
Smarter item picks cut Parkinson's tracking error by 34 percent
Optimized questionnaire item selection for tracking the progression of motor symptoms in Parkinson's disease
-
Decompose predictions to recover the true treatment effect
Prediction decomposition for causal analysis
-
Symmetric polynomials yield closed-form optimal FWER tests
Optimal multiple testing under family-wise error control: elementary symmetric polynomials and a scalable algorithm
-
Neural nets replace linear predictors in mixed-effects models
Neural Generalized Mixed-Effects Models
-
Bounds quantify error from restricted DAG search in MCMC
Restricted Search Space Graph MCMC via Birth-Death Processes
-
Neural net inside logit model uncovers hidden conjoint preferences
Learning Preferences from Conjoint Data: A Structural Deep Learning Approach
-
Tripartite models track actor-reference-keyword events in science
Modeling Tripartite Hyperevents in Scientific Collaboration Networks
-
Shared comparator combines trials for sharper treatment rules
Integrative learning of individualized treatment rules from multiple studies with partially overlapping treatments
-
Framework decomposes spillover mediation effects in cluster trials
Causal mediation in cluster-randomized trials with multiple mediators: spillover-aware decomposition, identification, and semiparametric efficient inference
-
Imputation choices barely shift EHR study results
Multiple Imputation Diagnostics when using Electronic Health Record Data in Observational Studies: A Case Study
-
Fréchet correlation ranks predictors by variance reduction
The Fr\'echet correlation coefficient for heterogeneous random objects
-
Orthogonal risk functions extend to conditional OR and RR
Orthogonal machine learning for conditional odds and risk ratios
-
Deep learner estimates time-varying treatment effects under censoring
Estimating heterogeneous treatment effects with survival outcomes via a deep survival learner
-
Debiasing produces valid confidence intervals for tensor estimates
Uncertainty Quantification for Noisy Low-tubal-rank Tensor Completion
-
Causal frameworks let RCTs and real-world data yield credible yet relevant evidence
Considerations for the Integration of Randomized Controlled Trials and Real-World Data
-
Different GGM methods yield varying AD brain connectivity estimates
Gaussian Graphical Models for Functional Connectivity Analysis: A Statistical Review with Applications to Alzheimer's Disease
-
Set projections replace latent variables for faster Bayesian sampling
Bayesian Distance-to-Set Models: from Latent Variable to Latent Projection
-
Cox partial likelihood averages risks for censored covariates
Cox Model Predicting Covariate Subject to Right Censoring
-
RDS now adjusts prevalence estimates for multiple recruitment traits
Inference from multivariate differential recruitment in respondent-driven sampling data
-
Byzantine identification enables exact decentralized convergence
Toward Exact Convergence in Byzantine-Robust Decentralized Learning: A Statistical Identification Approach