Latest Articles for Statistics

A new estimator improves analysis of complex datasets with multiple outputs and noise.

Learn how to combine evidence processes in data analysis effectively.

Study reveals key properties of inhomogeneous random matrices and spectral outliers.

Addressing fairness in machine learning for better statistical outcomes.

Explore how retrodiction connects past events to current understanding in various fields.

DiffRed combines techniques to simplify data analysis and improve results.

A look at how Brownian motion trees model trait evolution.

Learn how Bayesian methods improve predictions using past data.

A new approach emphasizes valid approximations over searching for truth in models.

Exploring the interplay between fractals and random fields.

Exploring methods to enhance multiclass classification through surrogate loss techniques.

Learn about Stochastic Localization in sampling and its key processes.

Exploring techniques to improve multiclass classifiers amidst mislabeled data challenges.

A study examining how particles interact, flow, and fluctuate over time.

A method to ensure balanced groups in experiments for fair results.

This study examines the reporting of linear regression assumptions in health research.

New methods improve efficiency and accuracy in tree building.

Introducing a method for density estimation using B-spline Hermite quasi-interpolation in clustering.

A look at how information theory measures and processes data.

This article delves into hitting distributions within random dynamical systems.

A new approach to linear bandits addresses feedback noise for better decision-making.

Improving model efficiency with new active learning techniques for incomplete data.

GhostKnockoffs enhances variable selection using summary statistics in genetics and beyond.

Introducing DOPE: a robust method to improve treatment effect estimation using observational data.

New measures improve comparisons of complex medical data sets.

Learn how Histogram Loss improves regression predictions by modeling uncertainty.

A new algorithm enhances detection of exchangeable factors in factor graphs.

New SWAP method improves understanding of spin glasses through enhanced relaxation dynamics.

Learn how partial feedback can streamline mode estimation in large datasets.

New methods for estimating random event processes from limited data.

Exploring new methods in algebraic statistics across educational testing, regression, and contingency tables.

Analyzing causes of performance differences in machine learning applications across various settings.

A novel method for accurate population size estimation with limited data.

This article examines the complexities and limitations of sparse linear regression methods.

A new method helps tackle tough statistical inference issues using artificial samples.

Study of how random-size arcs cover a one-dimensional torus over time.

Analyzing the complications of extrapolating completely monotone functions amid noisy data.

Investigating the challenges of sparse linear regression through lattice problems.

Learn how AutoCD simplifies finding causal relationships in data.

A new method enhances variational inference efficiency and accuracy.