Latest Articles for Statistics

Explore the benefits and applications of conformal hyperrectangles for reliable predictions.

Study reveals privacy concerns affecting census participation in subsidized housing.

A method merging Gradient Boosting and Mixed Effects for precise area-level predictions.

Learn how VPR improves efficiency in Bayesian inference by updating prior information.

Learn how to estimate entropy while managing limited memory resources.

A new approach to improve prediction reliability in machine learning.

A look at how empirical processes help analyze data in various fields.

This paper discusses fractals, their properties, and significant conjectures in the field.

Introducing a model that combines tree-based transforms for effective outcome generation.

Introducing new solvers for efficient optimal transport in machine learning.

Exploring efficient statistical methods for better predictions in machine learning.

A detailed look at the performance of the Least Squares Estimator under constraints.

Examining the role of clear definitions in statistical analysis.

An analysis of positive areas in spherical fractional Brownian motion.

This article examines the relationship between stretched Brownian motion and Bass martingales.

A method to enhance model accuracy by accounting for uncertainty in variables.

Discover how digital nets improve efficiency in complex mathematical tasks.

A look at various types of convergence in signed measures.

Learn how to classify incomplete data in knowledge graphs using Naive Bayes classifiers.

Learn how boosted conformal prediction enhances understanding of uncertainty in models.

A look into binary graphical models and their applications in neuroscience.

Introducing Treeffuser for improved probabilistic predictions from tabular data.

A novel approach to analyze the interplay of network data and covariates.

A guide to the Inlamemi R package for handling data challenges.

A look into the Kummer distribution and its role in free probability.

Bayes factors help researchers evaluate and compare hypotheses using data-driven evidence.

An overview of probabilistic graphical models and their applications in various fields.

Introducing Coupled Covariances Eigenproblem (CCE) for improved learning from asymmetric data.

A new method improves decision-making through historical data analysis.

A new approach enhances MCMC sampling efficiency using Riemannian geometry.

Explore strategies for making optimal choices in random decision-making scenarios.

Researchers improve reliability testing of one-shot devices using innovative statistical methods.

New algorithms enhance sampling from known and unknown distributions for practical applications.

This article discusses innovative methods for better statistical analysis of grouped data.

Percolation methods help reveal the connections among galaxies and their distribution in the universe.

Explore key estimators for linear regression and their impact on predictions.

Exploring the role of limit theorems in Gaussian random fields, especially in finance.

A concise overview of factor regression models and their applications.

A new approach enhances data distribution modeling on complex shapes.

A look into marginal optima and their impact on algorithms in complex systems.