Latest Articles for Statistics

Explore how the Feynman-Kac formula aids in studying complex changing systems.

Introducing a method to improve clustering of distributional data using averages and variations.

Examining the behavior of characteristic polynomials in random unitary matrices.

A new approach for effective dimension reduction in classification tasks.

Research focuses on improving machine learning defenses against adversarial attacks.

Analyzing how averaging shapes number distributions over time.

Examining techniques for modeling and understanding multiscale systems using SDEs and parameter estimation.

Analyzing how individual traits affect medication responses through statistical methods.

This article explores the significance of matchings in random graphs and their applications.

New methods improve accuracy in measuring distances between data points.

Investigating faster methods for two-sample testing using random Fourier features.

Learn how hyperbolic spaces improve data modeling for complex structures.

Learn how dimension reduction helps manage complex data effectively.

Benford's Law reveals odd patterns in first digits across data sets.

This study improves classifier performance through targeted strategies in Multi-Instance Partial Label Learning.

A new method for better prediction sets using multiple score functions.

A new method improves causal discovery accuracy using automated kernel selection.

Introducing a Bayesian method for inferring hidden states in complex systems.

Research explores how to estimate statistics while respecting user privacy needs.

New methods to compute geodesics on the Stiefel manifold enhance algorithm efficiency.

New algorithm enhances elliptical slice sampling for truncated distributions.

New methods improve confidence sets in high-dimensional statistics.

A tool for simultaneous variable selection in Bayesian regression models.

A look at the significance of subweibull distributions in data analysis.

A new framework connects theory with practice in machine learning.

Examining Fisher's experiment on tea and milk distinction provides insights into hypothesis testing.

A flexible approach to understanding irregular sequence behaviors in mathematics.

MGMC method improves efficiency in sampling complex Gaussian distributions.

A new method enhances learning from complex data using Wasserstein proximals.

Learn how Bayesian inference updates beliefs with new evidence.

Methods for transforming complex data into clear visual formats.

Learn how quantile regression and MM algorithms improve data analysis across various fields.

This paper discusses creating confidence bands for spectral density in stationary time series.

Learn how population data enhances prediction accuracy in uncertain models.

Calibration helps improve accuracy in disease spread models for better health decisions.

This study examines the impact of mean and median brightness on Cepheid distance calculations.

A look into the behavior of stable processes near geometric boundaries.

This article examines Bayes posteriors in nonlinear inverse problems from a frequentist view.

A new Bayesian approach enhances Gaussian processes for better prediction and uncertainty handling.

New confidence sequences improve uncertainty estimation in statistical models.