Latest Articles for Statistical Methods

New methods for identifying significant changes in data variance over time.

A look at causal machine learning methods and their impact in complex studies.

This research investigates the role of side information in identifying community structures.

A new method addresses selection bias in treatment effect estimation.

Exploring material durability and lifespan prediction methods in high-stress environments.

Reshuffling data splits enhances hyperparameter optimization in machine learning.

Strategies to manage missing data in biomedical research on competing risks.

A fresh approach to quantify uncertainty in complex data through mixture-based methods.

A new method simplifies variable selection in large datasets.

Gaussian Mixture Models improve predictions in particle physics by addressing data tensions.

A new method estimates parameters of neuron activity using real data.

New kernels enhance data analysis through complex function interactions.

This paper presents a new framework for enhancing randomization in clinical trials.

A fresh method for examining policy effects on event durations using hazard rates.

Improving optimization methods through UCB in local Bayesian strategies.

New methods improve the study of complex cosmological data through machine learning.

A fresh approach to gauge model accuracy without labels during data shifts.

Introducing a method that integrates machine learning with traditional statistics effectively.

This article discusses methods for identifying causal links in linear non-Gaussian models.

A new method for combining inconsistent measurement data shows promise for scientists.

A new method improves accuracy in predicting state transitions using Markov chains.

Discover how Stein Random Features enhance data analysis and prediction accuracy.

A guide to improving survival model selection in health economic evaluations.

Researchers use NN-CDFs to study neutrino sources more effectively.

This article examines the limitations of in-context learning in large language models.

This study examines methods to enhance text classification using SVM and kernel functions.

A new approach combining generative modeling and boosting for better learning outcomes.

This article discusses enhancing kernel ridgeless regression using LAB RBF kernels.

Enhancing prediction sets when data conditions shift without needing labels.

Learn how rerandomization and covariate adjustment improve accuracy in experiments.

Learn how businesses use statistical models to assess marketing campaigns effectively.

New framework improves accuracy in Bayesian measurement with limited data.

A look at methods for estimating treatment effects using real-world data.

A look at how populations mix and change over time through genetics.

A method for identifying regimes in complex data models.

Learn how step size affects gradient descent in logistic regression.

Examining methods to analyze jets from high-energy particle collisions.

Learn how importance weighting enhances model performance amid covariate shifts.

Examining better methods to analyze health treatment trials.

Introducing a new method for Bayesian neural networks that improves uncertainty modeling.