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1584 papers in stat.ME · page 10
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Ranked set sampling improves quantile estimator efficiency
L-Estimation of Population Quantiles Using Ranked Set Sampling
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Metric counts minimum decision changes to nullify causal result
Minimum Specification Perturbation: Robustness as Distance-to-Falsification in Causal Inference
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Source data stabilizes conformal prediction sets
Stable Localized Conformal Prediction via Transduction
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One summary share fits GLMMs without raw data
Federated generalized linear mixed models based on one-time shared summary statistics
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The paper proposes a new calibration technique for flavor taggers in particle physics…
Data-Driven, Geometry-Aware Optimal-Transport Calibration of Flavor Tagger
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MMAD depth matches classical methods with directional insights
Exploring Multivariate Data Using Median Absolute Deviation Depth
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Parallel subset chains boost MCMC sampling for multimodal targets
Modular Markov chain Monte Carlo with application to multimodal sampling
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LSE-GPQ intervals give reliable small-sample coverage for log-logistic reliability
A Novel Exact Inference Approach for Log-Logistic Reliability Functions with Applications to Time-to-Event Data
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Coarse-to-fine GLMM resolves degeneracy in large spatial count models
Coarse-to-fine spatial GLMM for scalable prediction and multiscale analysis
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Parametric start plus correction beats pure kernel density estimates
Nonparametric density estimation with a parametric start
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Graphical criteria guide covariate selection for DiD parallel trends
A formal approach to variable selection in difference-in-differences
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Energy distance scan detects single change points with permutation calibration
Single Change-Point Detection via Energy Distance with Application to Genomic Data
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Prior knowledge cuts spurious change points in time series
Pi-Change: A Prior-Informed Multiple Change Point Detection Algorithm
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SBI for f_NL passes coverage tests but gives underconfident posteriors
Coverage is not enough: Frequentist tests of simulation-based inference for primordial non-Gaussianity
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Spatial graph weights improve sparse recovery in high-dimensional VAR
High-Dimensional Multivariate VAR Estimation with Spatio-Temporal Structure
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Virtual particles enable MLE for mean-field limits from one trajectory
Recursive Maximum Likelihood Estimation for Interacting Particle Systems using Virtual Particles
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WT transitions filter GCMs better than daily frequencies
Evaluating the performance of GCM trajectories using Weather Type frequencies for persistence and transitions: the Iberian Peninsula and Lamb classification
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LLM agents trade 76 assets autonomously for five days
AgenticAITA: A Proof-Of-Concept About Deliberative Multi-Agent Reasoning for Autonomous Trading Systems
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Three-step method speeds up longitudinal function regression
Efficient Longitudinal Function-on-Function Regression
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Spatial medians and automatic exclusion stabilize high-dimensional clustering
Sparse $K$-spatial-median clustering for high-dimensional data
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Ego-cluster design estimates treatment and spillover effects in networks
Estimating Treatment and Spillover Effects with the Ego-Cluster Experimental Design
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A Fisher-consistent redescending M-estimator for spatial scalar-on-function regression is…
Robust spatial scalar-on-function regression: A Fisher-consistent redescending M-estimation approach
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Predictive Bayesian credible sets can have near-zero coverage
Concentration and Calibration in Predictive Bayesian Inference
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Workflow turns raw measurements into defensible ECE/CS results
How to Do Statistical Evaluations in ECE/CS Papers: A Practical Playbook for Defensible Results
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Generalized posterior designs need simulations at only two sample sizes
Economical Experimental Design with Generalized Posteriors
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Binomial flows give discrete diffusion models exact likelihoods
Binomial flows: Denoising and flow matching for discrete ordinal data
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Joint priors add correlations while keeping marginals fixed
Beyond Independence: on Jointly Normal Priors in Bayesian Inversion
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Simpler derivation standardizes person-fit statistics
Simplicity Above Elegance: Another Look at the Asymptotically Correct Standardization of Snijders
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Bivariate observation simplifies stock return MLE to regression
Modeling Stock Returns and Volatility Using Bivariate Gamma Generalized Laplace Law
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Kernel tests for independence work with weakly dependent data
Kernel-based independence and mean independence tests for weakly dependent data
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Adaptive estimation improves survival analysis in stratified trials
Data-Adaptive and Model-Robust Covariate Adjustment for Time-to-Event Outcomes in Stratified Randomized Trials
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Bayesian methods remain physically inconsistent
Response to: "A note on conditional densities, Bayes' rule, and recent criticisms of Bayesian inference" by Yan et al., 2026
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Sign-flipping test validates fixed effects in multivariate mixed models
Multivariate mixed models with model-free random effects
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Penalized mixtures recover true effect distributions without normality
Meta-Analysis Without Normality: Estimating the True Effect Distribution with Penalized Gaussian Mixtures
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Fixed-dimensional MCMC performs Bayesian variable selection without jumps
Reversible Jump MCMC With No Regrets: Bayesian Variable Selection Using Mixtures of Mutually Singular Distributions
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One high-precision observation tests uniformity on [0,1]
Single-Observation Uniformity Testing under Increasing Precision via Lacunary Harmonics
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One precise observation tests uniformity via lacunary harmonics
Single-Observation Uniformity Testing under Increasing Precision via Lacunary Harmonics
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Random shifts deliver exact tests for spatial regression covariates
Robust Nonparametric Testing Approaches for Spatial Regression
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Shift tests with corrections are asymptotically exact in spatial regression
Robust Nonparametric Testing Approaches for Spatial Regression
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Density power divergence downweights outliers in diagnostic meta-analysis
Robust inference methods of diagnostic test accuracy meta-analysis for influential outlying studies via density power divergence
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Alternating updates enable normal inference on covariates in latent models
Inference on Generalized Latent Variable Models with High-Dimensional Responses and Covariates
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Lie algebra truncation enables covariate-driven GP deformation prediction
Predicting Covariate-Driven Spatial Deformation for Nonstationary Gaussian Processes
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Elevated amyloid shortens remaining dementia-free quantiles
Bayesian Nonparametric Causal Inference for Quantile Residual Life: An Application to Alzheimer's Disease
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Neural network picks regression variables using OLS estimates
Linear Models, Variable Selection, Artificial Intelligence
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HyCNNs approximate quadratics with exponentially fewer parameters
Hyper Input Convex Neural Networks for Shape Constrained Learning and Optimal Transport
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ANOVA test and FDR selection identify volatility covariates
Nonparametric Testing and Variable Selection for ARCH-m(X) Model
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Bootstrap replicates MLE distribution in nonlinear panel models
Bootstrap Inference in Nonlinear Panel Data Models with Interactive Fixed Effects
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The paper extends the Minimum Covariance Determinant estimator to interval-valued data…
Minimum Covariance Determinant Estimator and Outlier Detection for Interval-valued Data
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CARhy tests circadian rhythm differences across multiple conditions
CARhy: Comprehensive Analyses of Circadian Rhythms in Transcriptomic Experiments with Multiple Conditions
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The paper introduces a framework for constructing Neyman-orthogonal scores in…
Flexible semiparametric modeling with application to Causal Inference