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1584 papers in stat.ME · page 14
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Student-t approximation for mixed estimated and analytic covariances
On combining estimated and analytic covariance matrices
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Random rewards extend phase-type models to latent severity
Random Reward Phase-Type Distributions with Applications in Latent Severity Modeling
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Asymptotic e-processes bound excursions uniformly up to growing horizons
Asymptotic e-processes
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Asymptotic e-processes bound excursions up to finite horizon r_m
Asymptotic e-processes
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QR reparametrization diagonalizes conditional Fisher matrix for NSS curves
Orthogonal reparametrization of the Nelson-Siegel-Svensson interest rate curve model: conditioning, diagnostics, and identifiability
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ASCA turns ANOVA into a multivariate tool for designed experiments
From design of experiments to analysis of variance of multivariate data: a tutorial review on ANOVA simultaneous component analysis
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ASCA extends ANOVA to high-dimensional DoE data
From design of experiments to analysis of variance of multivariate data: a tutorial review on ANOVA simultaneous component analysis
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Multiscale tables extend CMH test to continuous data
Multiscale Cochran-Mantel-Haenszel Scanning for Conditional Dependency
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Mixture model corrects bias in early failure predictions
A Finite Mixture Failure-rate based Heterogeneous Step-stress Accelerated Life Testing (h-SSALT) Model
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Mixture model corrects bias in step-stress lifetime predictions
A Finite Mixture Failure-rate based Heterogeneous Step-stress Accelerated Life Testing (h-SSALT) Model
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Transfer learning widens eigenvalue gaps to sharpen network estimates
Transfer Learning for Degree-Corrected Mixed Membership Network Models
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Excluding neighbourhoods sets loss-based priors by local KL geometry
The General Formulation of Loss-Based Priors for Parameter Spaces
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Clients share context-to-design mappings to cut experiments in Bayesian optimization
Collaborative Contextual Bayesian Optimization
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V_AR variance estimator fixes overcorrection in small-N penalized GEE
Overstuffed sandwiches and separation anxiety: finite-sample variance estimation for penalized GEE with near-separated binary data
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New mixture model makes large-scale spatial extreme analysis feasible
Spatial Extremes at Scale: A Case Study of Surface Skin Temperature and Heat Risk in the United States
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Simulations settle conflicting MANOVA error-rate reports
A simulation study to resolve conflicting evidence on the error rates from MANOVA group tests
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Causal scores mislead
Beyond Coefficients: Forecast-Necessity Testing for Interpretable Causal Discovery in Nonlinear Time-Series Models
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Joint Bayesian model improves spatial gene detection accuracy
JASPER: Joint Bayesian Analysis of Spatial Expression via Regression
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Estimator counts factors in high-dimensional data with missing values
Missingness-Adaptive Factor Identification in High-Dimensional Data
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Empirical Bayes pools multiple causal estimators for consistency
Shrinkage through multiple identifiability
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Regression composition yields order-dependent results
Order Dependence in Regression by Composition: Discussion on "Regression by Composition'' by Farewell, Daniel, Stensrud, and Huitfeldt
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Local f-squared shows what each predictor adds in marketing models
Effect Sizes in Marketing Research: Why Cohen's Local f^2 Belongs in the Toolkit
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Win statistics procedures control type I error in cluster trials
Statistical inference with win statistics in cluster-randomized trials with composite outcomes
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MD and MBN corrections fix coverage in stepped-wedge trials with varying effects
Which Small-Sample Correction Should Be Used When Analyzing Stepped-Wedge Designs with Time-Varying Treatment Effects?
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Embedding selection rules in simulators fixes Bayesian bias
Overcoming Selection Bias in Statistical Studies With Amortized Bayesian Inference
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Obvious causal links let observational data answer causal questions
Embarrassingly Causal: Causal Use of Associational Data in Magic The Gathering Drafts
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Markov transform enforces covariance structure in functional data
Inference for Functional Data under Markov Constraints
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New method estimates full return distributions at no extra sample cost
Distributional Off-Policy Evaluation with Deep Quantile Process Regression
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INLA hierarchy models non-linear BMI effects on mortality
Efficient Bayesian inference for non-linear association structures in joint models: A hierarchical approach via INLA
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Ensemble of kriging models improves multi-fidelity emulation
An ensemble-based approach for multi-fidelity emulation and adaptive sampling
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Bayesian prior controls FDR in high-dimensional Gaussian graphs
A Bayesian framework with adaptive elastic nets for the inference of Gaussian graphical models
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Local parametric fits reduce bias in kernel density estimates
Locally parametric nonparametric density estimation
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Federated RuleFit matches centralized accuracy on medical data
Federated Rule Ensemble Method in Medical Data
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Regularized Jensen-Shannon measures bound direct correlation to [0,1]
How to quantify direct correlations between variables
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Subbagging stabilizes ML predictions across random seeds
Improving reproducibility by controlling random seed stability in machine learning based estimation via bagging
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Subsampling breaks under dynamic contamination
Subsample-Based Estimation under Dynamic Contamination
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Simple removal of bad data fails to fix dynamic estimates
Subsample-Based Estimation under Dynamic Contamination
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Anchor estimator withholds unstable meta-analysis estimates
Stable Transport Meta-Analysis for Heterogeneous Cardiovascular Trials: A Nuisance-Anchor Framework with a Sign-Stability Diagnostic
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Lasso screening before optimization aids high-dimensional portfolios
Post-Screening Portfolio Selection
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Covariance explains Mapper communities in four datasets
A Null Model for Mapper Subtype Claims
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Gaussian mixture learning spots breast cancer metastases in slides
Detecting Breast Carcinoma Metastasis on Whole-Slide Images by Partially Subsampled Multiple Instance Learning
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Smooth surrogates turn AIC/BIC selection into continuous optimization
Model Selection and Parameter Inference through Constraints via Sequences of Surrogate Smoothing Functions
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Fourier test validates computer models globally and locally
Statistical Validation of Computer Models: Global and Subdomain Hypothesis Testing
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Clustering cleans PU labels when SCAR assumption fails
A proposal for PU classification under Non-SCAR using clustering and logistic model
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Kalman recursions yield L1 regularization paths on factor graphs
L1 Regularization Paths in Linear Models by Parametric Gaussian Message Passing
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Covariance split lets SEM work with more variables than samples
Covariance-Based Structural Equation Modeling in Small-Sample Settings with $p>n$
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Overlapping experiments yield corrected and combined effect estimates
Multi-Experiment Analysis
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Horseshoe prior matches exact minimax rates for sparse predictive inference
Horseshoe Predictive Inference
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Strang splitting gives consistent estimates for nonlinear Pearson SDEs
Strang splitting estimator for nonlinear multivariate stochastic differential equations with Pearson-type multiplicative noise
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Network meta-analysis covariances equal geometric series of diffusion matrices
Network Meta-analysis and Diffusion