Latest Articles for Statistics

Using matrix completion to improve time-series data accuracy.

Localized drift poses a challenge for predictive models in changing data streams.

Exploring the behavior and structure of random graphs in various contexts.

New methods enhance statistical analysis of non-stationary time series data.

Ultrahomogeneous graphs showcase symmetry, impacting various fields like computer science.

Exploring the patterns and properties of binomial coefficients and their significance.

New methods simplify calculations for precision matrices in large datasets.

Addressing class imbalance in clustering with innovative techniques.

A look into the importance and techniques for analyzing directional data.

New techniques improve value estimation from Markov chain data.

Accurate predictions depend on proper calibration to match probabilities with actual outcomes.

Exploring flexible priors to improve predictions in Bayesian Last Layer models.

Exploring how independence preserving maps influence random processes and models.

Learn how signatures simplify complex data for better insights.

fastkqr enhances quantile regression speed and accuracy while managing crossing issues.

Introducing a novel algorithm to identify causal relationships amidst hidden variables.

Explore the interaction between finite free probability and polynomial behavior.

This study examines the behavior of the smallest eigenvalue in random matrices affected by outliers.

Introducing a robust test for assessing elliptical models in high-dimensional datasets.

Learn how to create effective visuals for statistical model checks.

Understanding infer-and-widen and split-and-condition for improved statistical conclusions.

Examining the role and properties of prime numbers in various mathematical fields.

A look at combining probabilities and their applications in various fields.

A clear look at bivariate copulas and their role in modeling relationships between random variables.

A deep dive into the properties and applications of LSL copulas.

Examining the impact of data removal on MCMC analysis conclusions.

Explore the significance of acceptance rate in the Metropolis algorithm for sampling.

Introducing a method to identify outliers in categorical datasets.

Exploring how noise affects regression models and their predictions.

A look at generalized Frechet means and their role in modern data analysis.

A new method enhances classification by adjusting models to evolving data patterns.

New methods combine density estimation and deep learning for effective anomaly detection.

Recent findings uncover patterns in prime distributions within arithmetic progressions.

A look into how we find cause-and-effect relationships in data.

A new method enhances the analysis of point distributions in various fields.

Explore the role of eigenvalues in improving statistical analyses and model evaluations.

Explore how matrix recurrence relations impact stability in various fields.

Examining the impact of learning rates on predictive performance.

A new approach to enhance classification accuracy using PAC-Bayesian theory.

FastEnsemble improves speed and accuracy in data grouping methods.