Latest Articles for Statistics

This article presents a method to test independence in categorized data.

Innovative approaches improve the analysis of complex time series data.

Exploring the PAC-Bayesian framework's impact on machine learning generalization.

A new method for better estimating relationships in high-dimensional data.

A study on improving prediction accuracy for regression models.

This article examines particle movement in confined systems and its implications.

A cautious approach to selecting causal models improves research accuracy.

Introducing a method for selecting subdata to improve classification accuracy.

A look at the Inexact Regularized Proximal Newton Method and its significance.

A new method for identifying local causal relationships in data.

CAVIAR transforms how categorical variables are analyzed, improving outcomes in various fields.

A method to enhance the accuracy of statistical estimates efficiently.

A new method identifies variable interactions in complex time series data.

A new method for efficiently modeling complex Gaussian mixtures.

A new approach to clustering improves handling of tabular data.

A fresh framework for studying point processes using random measures and functional analysis.

A look at e-values and their role in hypothesis testing.

Examining how in-distribution labels impact out-of-distribution detection in machine learning.

A clear look at why switching doors is the winning strategy.

A new method to improve predictive models using uncertain data.

An overview of ergodic theory and its applications across various fields.

Exploring sequential testing methods for effective decision-making in statistics.

Exploring the significance and applications of non-Hermitian random matrices and their eigenvalues.

An overview of how particles behave independently in large systems.

Explore the role of GLMMs and PQL in analyzing complex data.

A fresh approach to compositional data classification using discriminative models.

New techniques improve Bayesian inference in Hidden Markov Models for better data analysis.

A look at threshold regression and its impact on high-dimensional data analysis.

Learn about an efficient method for calculating left-tail rare event probabilities.

New methods improve the efficiency of sampling from convex bodies.

New techniques improve image reconstruction from limited data.

Examining the concept of orthogonality in dynamical systems and its significance.

This study discusses methods to approximate complex equations with interacting particle systems.

A new algorithm enhances sampling efficiency in tree-based Bayesian models.

Introducing a framework that improves reliability analysis efficiency for rare events.

Exploring how causation probabilities impact student outcomes and teaching methods.

Introducing a fresh approach to analyze time series data in metric spaces.

This study reveals how individual data points impact machine learning model performance.

This paper discusses methods to estimate parameters in second-order stochastic differential equations using real-world data.

A novel approach improves distance calculations on complex shapes for various fields.