Statistics

Research on organoid networks reveals new information about brain development.

A study on predicting top-performing basketball lineups using player statistics.

This article introduces a method for better understanding economic interactions during financial stress.

Exploring methods to improve Random Forest predictions in spatial studies.

Investment firms are leveraging machine learning for trading strategies in the Chinese futures market.

Assessing translation accuracy through human evaluation and inter-rater reliability.

This article examines why weather forecasts vary in accuracy across the United States.

A study on using the Birnbaum-Saunders distribution for better fatigue life estimates.

R's new color functions enhance data visualization for better clarity and accessibility.

A new approach for evaluating statistical models against skewed distributions.

Rang helps researchers document and recreate their computational environments for accurate analysis.

New non-diagonal metrics enhance Bayesian inference for neural networks.

A study on using the Birnbaum-Saunders distribution for better fatigue life estimates.

Analyzing the random connections in Erdős-Rényi networks reveals insights into network behavior.

A new Bayesian method for better predictions using co-data in clinical research.

This article examines techniques for assessing spatial data model performance.

A new model predicts parameters to speed up neural network training.

Learn how DRO and optimal transport improve decision-making amid uncertainty.

Techniques to enhance machine learning accuracy despite small datasets.

A novel approach to improve predictions of missing network connections.

Examining methods for finding small groups in extensive networks.

An overview of PAC learning and its applications in algorithm development.

Explore how sequential probability assignment aids in accurate predictions across various fields.

Exploring methods to improve Random Forest predictions in spatial studies.

This article presents a method to simplify estimating intensity in point processes.

This study explores changes in daily routines during the COVID-19 pandemic.

A look into how individual traits affect event timing in various fields.

A new approach for evaluating statistical models against skewed distributions.

Exploring how mechanical systems can function as hashing tools through load response.

This article introduces a method for better understanding economic interactions during financial stress.

A new model improves data analysis in crossover trials with skewed responses.

Leveraging prior knowledge in gamma regression to enhance estimates in complex data analysis.

Examining the reliability and validation of influence functions in deep learning models.

A new algorithm enhances accuracy in forecasting disease outbreaks through detailed data generation.

A discussion on merging statistical approaches for better data analysis.

A fresh approach uncovers individual variations in program treatment effects.

Methods to accurately calculate averages and variances despite missing data points.

A method for predicting specific outcomes using relevant past data.

A new framework for better statistical inference in research and analysis.

A fresh approach improves signal detection in noisy environments with limited data.

A new method improves parameter estimation in genetic models.

Exploring how to locate a key node in complex networks.

A new approach for evaluating statistical models against skewed distributions.

Examining methods for finding small groups in extensive networks.

An overview of quasirandom permutations and their significance in various fields.

A new model improves reliability assessment in health research.

New algorithms improve decision-making in environments with extreme rewards.

A new method improves PCA effectiveness in noisy and ill-conditioned data environments.