Latest Articles for Statistics

Exploring the behavior of eigenvalues in random matrices through the circular law.

Explore stationary-increment harmonizable stable processes and their applications in various fields.

Exploring new methods in event clustering analysis across various fields.

A look at how random walks help in understanding complex data changes.

New methods in conformal prediction enhance reliability for group outcomes.

A new method enhances prediction accuracy using leave-one-out cross-validation.

Bell numbers help us partition sets, revealing their mathematical significance.

This article discusses methods to handle bias in distance correlation.

A deep dive into Wasserstein projections and their applications in statistics.

A new approach enhances the accuracy of probabilistic classifiers in machine learning.

A look at the significance and applications of Dickman type processes.

A new method simplifies estimating connections between probability distributions.

Learn how kurtosis affects data behavior across various fields.

Introducing a new way to create features that improve model outcomes.

New approach improves regression estimates by effectively handling outliers linked to variables.

A look into the types and measurement of uncertainty in predictions.

Introducing SARIS: a method for estimating normalizing constants with improved efficiency.

An approach to simulate randomness in biological processes using advanced mathematical methods.

This article examines new methods for assessing Gaussian random vectors' concentration around average values.

Learn how likelihood ratios and p-values differ in hypothesis testing.

An overview of dynamic ASEP and its key concepts.

New methods improve efficiency in high-dimensional kernel approximations using Fourier features.

This article discusses new methods for efficient data analysis using Bayesian techniques.

A look into leveraging distributed learning while ensuring data privacy.

A new model addresses challenges in ranking with changing data.

This article presents a novel approach to kernel quantile regression using random features.

Exploring bifiltrations for improved data analysis and outlier management.

Examining how added variables influence statistical significance in research findings.

Orthogonal polynomials offer unique properties useful in various mathematical applications.

Exploring the significance of characteristic polynomials in random matrix theory and number theory.

An analysis of how entry distribution affects the bottom singular vector.

A new method for estimating true distributions from noisy streaming data.

Introducing a robust method for hypothesis testing with corrupted data.

A study on using tree structures to enhance topic modeling in text data.

This study examines how data quality affects AI-generated visualizations.

A new approach for handling complex data with statistical analysis.

A look into RAI within the multi-armed bandit framework to optimize decision-making.

MENSA enhances survival predictions by handling multiple events and censoring effectively.

A new method for detecting abnormalities in brain injuries shows promising results.

A guide to methods for estimating asymptotic covariance in MCMC simulations.