Statistics

A Bayesian framework improves accuracy in analyzing protein levels in biological studies.

Introducing weighted conformal p-values for effective candidate selection in various fields.

Bayesian methods improve survey data analysis with sparse responses, enhancing reliability.

A study reveals significant underreporting of COVID-19 cases in Italy's first wave.

A new model improves predictions in microbiome research with limited data.

A novel approach to ensure fair predictions in urban mobility analysis.

AWAIRE offers a fresh approach to verify IRV election results without detailed records.

A look at how SHAP and CEN improve data analysis insights.

A guide to Bayesian analysis techniques for spatial data forecasting.

A new method improves clustering results and insights through balanced groupings.

A new method for estimating distributions using Bayesian histograms enhances memory efficiency.

A new model improves predictions in microbiome research with limited data.

A new method to calculate winning chances in major sports tournaments efficiently.

Learn about stochastic dominance and its application in investment analysis.

Discover how Gaussian graphical models analyze relationships in paired data.

A new method for drawing insights from summarized data using Gibbs sampling.

Study on the use of technology to analyze sports commentary for insights.

Learn how NSBM helps analyze unlabeled networks and detect communities effectively.

New decoding methods enhance quantum error correction, ensuring accuracy in complex computations.

A look at multicalibration and omniprediction in machine learning.

Batched prediction improves outcome assessments for groups of examples in research.

Introducing Variational Inference Thompson Sampling for efficient decision-making.

A new method improves clustering results and insights through balanced groupings.

Researchers apply machine learning to better understand phase transitions in materials.

A look at Haldane's rule and its impact on making predictions.

A method to assess asset performance beyond market expectations.

A guide to Bayesian analysis techniques for spatial data forecasting.

A Bayesian framework improves accuracy in analyzing protein levels in biological studies.

Introducing weighted conformal p-values for effective candidate selection in various fields.

Learn how NSBM helps analyze unlabeled networks and detect communities effectively.

Bayesian methods improve survey data analysis with sparse responses, enhancing reliability.

Learn about factor models and their methods for simplifying complex data.

A look at Haldane's rule and its impact on making predictions.

An improved model for analyzing connections in bipartite networks.

Combining neural classifiers with Monte Carlo simulation improves data analysis methods.

A study on identifying factors affecting fertility rates across countries.

Learn how automation can simplify grading open-ended assignments for educators.

Overview of volatility models in geography, finance, and environmental science.

A look at Bayesian and Frequentist methods in statistics.

New spectral approach enhances multivariate Matérn models for spatial data analysis.

Introducing weighted conformal p-values for effective candidate selection in various fields.

Exploring the role of random matrices in statistical modeling and covariance estimation errors.

A method for estimating jump sizes in storage systems using non-parametric techniques.

A new method for estimating distributions using Bayesian histograms enhances memory efficiency.

A novel approach to simplify complex data analysis using optimal transport methods.

Researchers develop tests to assess diffusion coefficients in complex systems over time.

Explore how nonlinear meta-learning improves task learning efficiency and accuracy.

The rSVDdpd algorithm offers reliable data insights amidst outliers and noise.