Statistics

New methods enhance detection of quick, small optical events with improved efficiency.

This article examines the BAR method for variable selection in medical research.

Introducing a model that accounts for animal memory in population estimates.

cosimmr improves the study of animal diets with fast and insightful analyses.

New methods improve data accuracy in wind energy production.

A fresh approach enhances understanding of data relationships in machine learning.

Research improves accuracy of postmortem interval estimation using larger datasets.

This article outlines methods for detecting and localizing oscillations in power systems.

Nonparanormal models provide insights into complex, non-normal data relationships.

Studying how to group students for effective language placement tests.

A method to enhance simulations using Bayesian ideas and active learning.

Explore the psvmSDR package for efficient variable reduction in data analysis.

This study assesses the impact of social connections on individual outcomes.

A new method enhances temperature selection for efficient statistical sampling.

This article discusses dataset distillation and its importance in various fields.

Learn how agent-based modeling and random numbers aid health research.

A novel approach improves the accuracy of lithium-ion battery health assessments.

Exploring efficient algorithms for decentralized learning while preserving data privacy.

New methods enhance detection of quick, small optical events with improved efficiency.

Introducing p-dLDS: A fresh approach to understanding complex brain activity amidst noise.

Discover new methods to improve language models through balanced learning.

A look at kernel Kullback-Leibler divergence and its practical applications.

A new approach enhances prediction speed and accuracy in various fields.

New method improves sampling efficiency using energy functions.

Improved methods for assessing Pareto type-I distribution with censored data.

This article discusses the significance of measuring uncertainty in health data analysis.

This article examines the BAR method for variable selection in medical research.

Nonparanormal models provide insights into complex, non-normal data relationships.

Introducing a model that accounts for animal memory in population estimates.

Explores how stochastic differential equations enhance data analysis in various fields.

cosimmr improves the study of animal diets with fast and insightful analyses.

A new approach to estimate treatment effects considering social influences.

Examining how scatterers affect wireless signal quality in various environments.

Learn how motion affects wireless communication signals and their reliability.

Discover strategies to improve your odds in Hopscotch and Warships.

New forecasting methods enhance demand prediction accuracy and inventory management.

A guide to efficiently format academic submissions using elsarticle.cls.

A look at the Ornstein-Uhlenbeck process and its real-world applications.

New adaptive detection algorithms improve target identification in complex environments.

A new method improves estimation of population characteristics using mixed sampling data.

Improved methods for assessing Pareto type-I distribution with censored data.

This article discusses the significance of measuring uncertainty in health data analysis.

A look into variable selection methods for complex data analysis.

A look into kernel regression's challenges and insights in high-dimensional settings.

A new method enhances the analysis of functional data by accounting for directionality.

Discover methods to analyze complex, non-uniform data across different areas.

Patient-specific models enhance understanding of heart blood flow and treatment strategies.

New methods improve signal recovery from noisy data without noise distribution knowledge.