Latest Articles for Statistics

A fresh method for better data analysis in complex datasets.

Exploring magnetization and parameter estimation in complex systems.

A look into local empirical processes and their role in error control.

This article presents a method for obtaining multiple feature sets for predictive modeling.

Gibbs sampling enhances the efficiency of multi-object tracking, simplifying complex estimation processes.

Using PCR to analyze noisy data and enhance predictive accuracy.

IWA updates improve algorithm performance by making tiny adjustments based on task importance.

Research reveals new methods for fitting ellipsoids to random data points.

This article delves into improving methods for uncertain data optimization.

This article examines the isoperimetric problem and its significance in geometry.

This article discusses importance sampling and its role in maintaining data privacy.

New adaptive methods improve Bayesian inference with Hamiltonian Monte Carlo.

An overview of structured missingness in health research and its implications.

This article examines the moments of Artin-Schreier functions across different families of algebraic curves.

A new algorithm enhances the sampling of lattice points in polytopes.

A look at a card guessing game and its strategies.

An overview of challenges and strategies in multi-armed bandit problems.

A novel approach enhances prediction reliability in complex data analysis.

Examining the vulnerabilities of random rounding in Canadian census data.

Feature selection simplifies data analysis by identifying key variables.

Exploring the connection between neural networks and field theories for enhanced insights.

A look at how the geometric median aids in robust data analysis.

Explore survival probability's role in finance, insurance, and system stability.

A method for locating change points in piecewise polynomial models with uncertainty quantification.

Examining how incentives shape statistical practices in scientific studies.

Introducing a framework to simplify sparse regularization through smooth optimization techniques.

Exploring the structure and applications of balanced permutations in mathematics.

This paper explores misleading data connections and their impact on decision-making.

Learn about Hamiltonian Monte Carlo and its applications in statistics and science.

Learn how to assess model fit using methods like the Weibull distribution.

Exploring how Fermat distances improve data analysis and clustering techniques.

A new method for estimating diffusion coefficients using ridge estimators.

A look at new methods for efficient data recovery from low rank matrices.

A new approach improves deep learning models for nonparametric regression using adversarial training.

Learn about Spike-and-Slab Priors and their applications in Bayesian linear regression.

A look into the significance of permutations and patterns in data analysis.

This paper introduces methods for testing differences and detecting changes in non-Euclidean data.

New methods improve sampling efficiency and accuracy in statistics.

TimeGNN improves forecasting accuracy using dynamic graphs to capture changing relationships.

An analysis of decision-making in gambling with limited information.