Statistics

An overview of resilience events and their impact on electric power systems.

An overview of observational studies and linear regression analysis techniques.

New score matching methods address unique data types for improved statistical modeling.

Introducing a statistical model to improve glaucoma monitoring through macular thickness measurements.

Improving patient care through advanced statistical analysis of critical health data.

Explore the Tsallis-Gaussian distribution for modeling uncertainty in various fields.

Learn how to establish the right sample size for effective healthcare prediction models.

Researchers face challenges with the Dunnett procedure due to varying variances.

New score matching methods address unique data types for improved statistical modeling.

A new method improves graphical models by including covariate information for better accuracy.

Explore the Tsallis-Gaussian distribution for modeling uncertainty in various fields.

A new method helps cities gauge shared mobility demand accurately.

A method to reveal trends in functional data through clustering and segmentation.

Waywiser simplifies assessment of spatial models for reliable predictions.

Learn about Hamiltonian Monte Carlo and its role in sampling complex distributions.

A look into Generalised Linear Mixed Models and their applications.

A new approach enhances sparse coding for better data representation and analysis.

Track shifts in model explanations to maintain performance over time.

A simplified method for optimizing ad performance in online marketing.

Exploring reinforcement learning applications for complex nonlinear control systems.

This method uses kernel techniques to efficiently find ground states in quantum systems.

Strategies to enhance model performance in new data environments.

Introducing a method that improves image style transfer without extra training.

Learn how Mixup improves machine learning model training and performance.

This article examines methods for identifying causal links in high-dimensional data.

An overview of observational studies and linear regression analysis techniques.

Learn how expert insights improve Bayesian modeling with informative priors.

New score matching methods address unique data types for improved statistical modeling.

Learn to build contingency tables maintaining specific probabilities and relationships.

A new method improves graphical models by including covariate information for better accuracy.

Improving patient care through advanced statistical analysis of critical health data.

Learn how the multiscale penalty method identifies significant data shifts effectively.

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.

Learn how to enhance statistical tests for more reliable results.

An overview of how Laplace learning handles data labeling in machine learning.

New score matching methods address unique data types for improved statistical modeling.

Explore nonuniform bounds for Studentized U-statistics and their significance.

Exploring how misspecified priors can still yield reliable statistical estimates.

A new statistical approach improves analysis of genetic influences on metabolites.

A new method improves statistical analysis reliability amid model misspecification.

The Neural Frailty Machine improves predictions in survival analysis across various fields.