Latest Articles for Statistics

This article explores methods for estimating multivariate expectiles using functional covariates.

A look into how Gaussian mixed-effects models analyze time-dependent data.

A novel framework improves approximate inference in probabilistic graphical models.

Research aims to enhance data representation using nonlinear methods and temporal structures.

Learn how Ensemble Slice Sampling improves statistical sampling methods in complex models.

Examining weakly Markov categories and weakly affine monads in mathematical structures.

A discussion on merging statistical approaches for better data analysis.

A look at the relationship between skewness of multiple random variables under uncertainty.

An exploration of Mean Field Games and their applications in decision-making.

A look at how random assignments shape OLS regression outcomes.

A guide to selecting the right evaluation metrics for binary classification.

A mathematical method for analyzing complex data shapes and structures.

Exploring how walks in graphs influence various fields of study.

This article examines the challenges of ICA and explores methods for improvement.

A method for improved confidence intervals in monotone regression using SLSE.

A new method enhances understanding of data relationships in noisy environments.

A new method simplifies complex calculations in parametric Markov models.

New approach to improve prediction areas for time series using conformal prediction.

A look into constrained optimization and its real-world applications.

This article examines random colouring methods for sparse graphs and their implications.

Efficient techniques for minimizing complex functions in various fields.

Researching complex systems that change over time using nonlinear Markov chains.

Understanding complex interactions in datasets using tensor methods.

Explore the properties and applications of the Higher-Rank Askey-Wilson Algebra.

Learn how to evaluate parameter identifiability using a Bayesian approach.

An overview of techniques for filling missing values in long matrices.

Exploring the trade-offs between clustering quality and explainability.

Explore the benefits and applications of functional time series analysis.

Introducing a method to utilize unlabelled data in Bayesian Neural Networks for better predictions.

Combining clustering with topological analysis reveals hidden structures in high-dimensional data.

Researchers introduce innovative ways to analyze income inequality using generalized Lorenz curves.

A look at the benefits of VC-wTGS for complex data analysis.

Understanding and managing missing values is crucial for accurate healthcare data analysis.

Explore key operations and applications of multidimensional matrices across various fields.

SynthPop++ creates synthetic populations for better data-driven decisions.

OFTET combines traditional and machine learning methods for reliable time series predictions.

Exploring horospheres and their behavior in random geometric systems.

Introducing the PX-ECME algorithm for improved logistic regression performance.

Examining linear regression methods amid high-dimensional data and correlated noise.

An exploration of the Metropolis-Adjusted Langevin Algorithm's performance in sampling.