Latest Articles for Statistical Modeling

An overview of two-way clustering methods for better statistical results.

A method for effective analysis of high-dimensional tensor factor models in finance.

Study reveals how muscle activation affects mouse locomotion on a treadmill.

A flexible model for analyzing complex datasets with changing relationships.

A new method enhances neural networks for clustered data analysis.

A new model connects single and multiple event types for better analysis.

Introducing a flexible approach to understand relationships using observational data.

Exploring how linear state space models learn and what shapes their dynamics.

New method improves uncertainty quantification in data analysis.

Using advanced modeling to ensure safe infrastructure management.

Examining the challenges of interpreting linear regression models in machine learning.

Introducing a novel approach for better predictions in machine learning.

This article examines models connecting animal movement to population data.

New methods improve understanding of population dynamics through genetics.

A clear overview of factor models and their applications in various fields.

SOFA integrates guiding variables to enhance multi-omics data analysis.

A new method approximates neural networks for better uncertainty analysis.

This paper examines the behavior and challenges of mixture models in statistics.

New GMM-based pilot design enhances channel estimation in wireless systems.

A new framework enhances extreme value estimation using distributionally robust optimization techniques.

Introducing a model for better connections and clustering in networks.

This study improves economic predictions using Bayesian methods and a stochastic block model.

A look into the complexities of species diversification models and their implications.

A study introduces a reliable way to estimate allele frequencies from genetic research.

New methods enhance accuracy in machine learning with limited data labeling.

A novel approach to locate multiple sources in 3D space using TDOA measurements.

A new method improves data generation through adaptive tensor trees.

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

A new method enhances the performance of Bayesian neural networks through symmetrization.

Examining how averaged dynamics and randomness improve learning models.

A look at using statistical models to evaluate athlete performance.

Learn how Gaussian processes address prediction uncertainty in machine learning.

A new method reveals insights into prediction errors and model complexity.

A method to validate Tobit models by testing key assumptions.

A look at the complexities of normal mixture models in statistics.

MultiCOAP improves analysis of count data from multiple studies, addressing complexity and overdispersion.

A novel method improves Bayesian network learning from data.

New method enhances Gaussian process models for faster predictions with real-time data.

A look at CARMA processes and their simulation using tempered stable distributions.

Introducing SARIS: a method for estimating normalizing constants with improved efficiency.