Latest Articles for Statistics

A deep dive into stable sparse solutions in optimization.

Overview of randomization inference methods and their applications in research.

Learn how data augmentation algorithms improve data analysis and model building.

New methods enhance parameter estimation in spin glass models.

Learn about self-supervised methods for selecting key features in complex datasets.

Learn key concepts and techniques in data compression for efficient storage and transmission.

This article discusses the role of minimax procedures in enhancing linear regression accuracy.

A new approach for finding leading eigenvectors in complex matrices.

Introducing jointLCA, a method for better understanding multiview data connections.

A new method combines divide-and-conquer MCMC with diffusion models for better sampling.

A look at the concepts of probability and number approximations.

This study introduces a new algorithm for efficient function optimization using limited feedback.

This article discusses methods to sample from complex high-dimensional data more effectively.

Learn how kernel regression and Bayesian updating improve predictions with new data.

This research aims to clarify the mechanics of GCP and Riemannian metrics.

Introducing a Bayesian approach to improve variable selection in regression models.

A guide to optimizing subsample size for efficient data analysis.

Learn how vine copulas improve predictions in complex data relationships.

An overview of the Skorokhod problem and its significance in various fields.

A flexible approach to analyze complex datasets using Shared Atoms Nested priors.

Combine labeled and unlabeled data to enhance model accuracy.

A new method that combines strengths of Sliced and Tree Wasserstein for dynamic data analysis.

This article introduces minimax quantiles for better statistical estimates.

A look at record linkage algorithms and their impact on data analysis.

Researchers introduce a method to evaluate independence of random variables using quantiles.

Examining how two dimensions of random movement can influence each other.

Exploring the implications of the infinite pigeonhole principle in various fields.

PSVAE offers a faster method for creating high-quality synthetic tabular data.

Examining the role of equivariant modules in modern mathematical research.

Simplifying spatial data analysis with directed graphical models for yes/no outcomes.

Addressing confounding factors and shifts in data for better predictions.

A look at Markov random fields and their role in analyzing complex relationships.

A new method improves uncertainty estimation in machine learning applications.

Examining uncertain differential equations in dynamic systems and their real-world applications.

A look at how missing data impacts healthcare treatment evaluations.

Explore how circles can cover darts on a hexagonal board.

This article discusses a method for better predicting time series data uncertainty.

Examining how latent Gaussian models improve data analysis in public health and migration.

An overview of two-way clustering methods for better statistical results.

Explore the dynamics and implications of explosive behavior in SDEs.