Latest Articles for Statistics

Adaptive sample splitting enhances accuracy and reliability in predictive modeling.

Introducing SPCA to better handle complex datasets with repeated eigenvalues.

This article discusses non-parametric tests for analyzing symmetry in data.

Monte Carlo methods enhance predictions in physics, addressing challenges in simulations and parameter optimization.

An overview of moving average processes and their applications in real-world data.

Research on edge crossings in topological graphs reveals important structural insights.

A study of 2-bridge knots, focusing on genus and crossing numbers.

A new method enhances language model predictions using smaller example groups.

This article examines how randomness affects training outcomes in machine learning models.

A look at interval-closed sets and their toggling behavior.

Learn how density ratio estimation helps compare data groups effectively.

A look into Bayesian and frequentist approaches for estimating uncertainty.

Tackling missing data through innovative regression techniques for accurate insights.

New methods improve clustering of complex functional data.

Causal learning reveals cause-and-effect relationships in data analysis.

R enyi entropy helps quantify diversity in ecosystems and other complex systems.

Collider bias can mislead research findings about the connection between exposure and outcome.

CoxKnockoff enhances feature selection in survival analysis while controlling false discoveries.

A new statistical model improving data analysis across various fields.

Introducing the Lorenz P-P plot for assessing second-order stochastic dominance in distributions.

Beta-trees improve how we visualize and summarize complex, multidimensional data.

A look at the Max-U-Exp distribution and its role in mixed Poisson processes.

Explore how IML transforms data analysis into clear insights.

VC-dimension helps assess a model's learning ability from examples.

This study examines tobacco smoking patterns and influencing factors in India.

A look into how systems shift from disorder to order in Markov processes.

Learn how structural breaks impact predictive regression models in economics.

This article presents a new estimation technique for exponential distributions.

A new method for accurately estimating missing data in statistical analyses.

New techniques improve causal inference despite unobserved confounders and complex relationships.

A look at how covariance matrices connect data behavior and statistical principles.

An overview of V-monotone independence and its significance in probability theory.

This article discusses advanced techniques for detecting anomalies in multivariate time series.

New indices offer fresh insights into income inequality across different groups.

New methods improve understanding of random matrix behavior and dependencies.

Explores bandit feedback and its implications for machine learning models.

A guide to using Hidden Markov Models for analyzing time-dependent data.

Combining data analysis and model checking improves insights and decision-making.

Using data to forecast COVID-19 hospitalizations can improve healthcare planning.

Learn how covariance matrix estimation enhances financial decision-making and risk management.