Statistics

Researchers use machine learning to improve detection of internal solitary waves in ocean data.

Examining the divide between elites and the masses in political discussions online.

Using gene expression data to predict chemical impacts on health and environment.

Analyzing traditional and machine learning methods for handling missing data.

Learn how vine copulas improve predictions in complex data relationships.

A flexible approach to analyze complex datasets using Shared Atoms Nested priors.

Innovative methods to retrieve time labels from noisy dynamical data.

A look at record linkage algorithms and their impact on data analysis.

This article discusses methods to sample from complex high-dimensional data more effectively.

A novel approach to understanding stock interactions during market changes.

Bayesian methods improve data analysis speed and accuracy for large datasets.

A new method merges Bayesian inference and machine learning for better data analysis.

A new method for estimating conditional expectations efficiently in uncertain environments.

Examining how population models shape genealogies and influence genetic algorithms.

New techniques in sampling improve efficiency in statistical analysis.

A novel technique using electrostatics for better data sampling and estimation.

This article discusses methods to sample from complex high-dimensional data more effectively.

Exploring privacy risks in synthetic data and introducing the Data Plagiarism Index.

Federated learning enhances medical imaging while protecting patient data.

A new method combines Bayesian predictions and vine copulas for improved data analysis.

Investigating how mirror flow minimizes errors in classification tasks.

Learn how kernel regression and Bayesian updating improve predictions with new data.

Introducing PACE, a structured approach for trustworthy AI explanations.

New models improve predictions in changing data environments.

Introducing a Bayesian approach to improve variable selection in regression models.

A guide to optimizing subsample size for efficient data analysis.

Learn how Cluster Quilting addresses challenges in patchwork learning with incomplete datasets.

Analyzing traditional and machine learning methods for handling missing data.

Learn how vine copulas improve predictions in complex data relationships.

A fresh approach to understand causal effects in treatment studies with continuous variables.

A flexible approach to analyze complex datasets using Shared Atoms Nested priors.

A new method improves data modeling in areas with limited information.

This research develops methods for fair resource allocation despite limited user feedback.

A look into how the estimand framework improves clinical trial analysis.

A fresh approach to understanding complex human connections through fuzzy social network analysis.

A study on how Park-and-Ride can reduce congestion and emissions.

Information significantly impacts decision-making processes across various fields.

Benford's Law reveals odd patterns in first digits across data sets.

A method for detailed signal analysis over time and frequency.

New methods enhance understanding of the universe through weak gravitational lensing data.

This article discusses methods to sample from complex high-dimensional data more effectively.

Learn how kernel regression and Bayesian updating improve predictions with new data.

Innovative methods to retrieve time labels from noisy dynamical data.

This article introduces minimax quantiles for better statistical estimates.

This study examines Bayesian PINNs for estimating PDE parameters from noisy data.

Two new estimators enhance accuracy in analyzing item response data.

Explore how the stochastic block model helps identify communities in networks.

Learn how to identify unusual patterns in time-series data with Markov depth.