Latest Articles for Statistics

Learn how Bayes factors improve hypothesis testing and parameter estimation.

This article presents fresh methods to measure convergence in Markovian processes using Orlicz spaces.

Innovative methods for polynomial regression in noisy environments.

Exploring matrix perturbation impacts on data analysis in various fields.

A look into the unique challenges of analyzing compositional data accurately.

A new method enhances the analysis of count data in longitudinal studies.

Research on polynomial functions and their role in approximating high-dimensional Gaussian distributions.

Examining how LLMs can perform regression without additional training.

Exploring properties and behaviors of random centrosymmetric matrices and their eigenvalues.

Examining effects of extreme treatments on various outcomes across multiple fields.

A clear guide to matrices, their types, and uses in various fields.

A new approach boosts efficiency in analyzing conditional latent Gaussian models.

Exploring self-avoiding walks and their significance in group theory and applications.

A look at unitary operators, conjugations, and their impact on mathematics and technology.

A look at tropical Fermat-Weber points and their applications in various fields.

A look at how algorithms can respect data deletion requests while maintaining efficiency.

Exploring random sequences in mathematical structures and their properties.

This study examines compositional data and the importance of spatial analysis.

A method to solve complex optimization problems with nonlinear equality constraints.

A new model captures individual differences in count data analysis.

Explore essential probability distributions used in various fields and their applications.

NCL improves interpretability and performance in machine learning tasks.

Research identifies instances of cyclic sieving in permutation mappings using SageMath.

Improving information recovery through Bayesian methods in imaging and signal processing.

Introducing improved residuals for better analyzing compositional datasets.

Examining the properties and applications of stationary Gaussian fields in various disciplines.

This work introduces a new method for estimating diffusion processes using multilevel Monte Carlo techniques.

This article discusses enhancing Additive Gaussian Processes using a new approach called Kernel Multigrid.

A unified approach enhances accuracy in small area estimation.

A look into the weak Lefschetz property and its significance in random algebras.

New method improves estimation in statistics through robust techniques.

Exploring methods to recover model parameters from leverage scores in regression analysis.

New method aims to improve fairness in synthetic healthcare data generation.

This paper presents a novel strategy for improving regression tasks through active learning.

A look into causal relationships in quantum experiments and their implications for theories.

Combining diverse models improves predictions in functional data analysis.

A fresh approach to hypothesis testing in high-dimensional data contexts.

A look into PushTASEP systems and their behaviors using Macdonald polynomials.

A look into robust estimation techniques in statistics.

Methods for handling missing data in spatial autoregressive models are discussed.