Statistics

Examining how cryptocurrencies like Bitcoin and Ethereum relate to traditional financial markets.

Learn how A/B testing can improve business decisions and user experiences.

New insights on the Omicron variant's impact on public health.

This article explores skill models in darts using empirical Bayes methods for player analysis.

A new statistical approach enhances estimates of under-five mortality rates across different age groups.

Learn how machine learning helps predict vehicle insurance claims and set fair premiums.

A framework that improves the accuracy of soft sensors in industrial applications.

Research reveals varying impacts of air pollution on different groups.

SNAMs offer clearer insights into machine learning predictions.

A new method improves data classification using covariance matrix clustering.

Learn about key concepts in optimization and sampling for effective decision-making.

Discover innovative methods for analyzing longitudinal data using the lqmix R package.

RESI streamlines the reporting of effect sizes in research studies.

A focused approach to improving variational inference accuracy.

This study highlights methods for analyzing brain signals using covariance matrices.

Examining structures in data through connected clustering methods.

New sampling methods improve efficiency and accuracy in Bayesian Neural Networks.

This research investigates how Gaussian mixtures can enhance data modeling techniques.

A new method tackles endogeneity in online data analysis using Two-Stage Least Squares regression.

Examining SMD and SGD for better model generalization.

This article discusses methods to improve predictions with unbalanced data in regression.

Learn how manifold optimization improves machine learning algorithms and model performance.

A closer look at IBNNs and their role in managing uncertainty in machine learning.

This article highlights the role of non-separable kernels in Gaussian processes.

Introducing a method for better handling complex data relationships.

This article discusses methods to improve predictions with unbalanced data in regression.

An overview of two correlation methods and a new combined approach.

Research improves neural networks' ability to adapt to new data.

A tool for researchers to model changes in data over time.

New methods improve predictions for children's recovery after brain injuries using existing data.

A new statistical approach enhances estimates of under-five mortality rates across different age groups.

A new model improves how we study brain connectivity and its anatomical features.

New sampling methods improve efficiency and accuracy in Bayesian Neural Networks.

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.

This research investigates how Gaussian mixtures can enhance data modeling techniques.

This article highlights the role of non-separable kernels in Gaussian processes.

iPCA offers a reliable method for analyzing grouped data relationships.

Explore methods for reliable predictions in machine learning through confidence sets.

A look into excess risk and empirical risk minimization with exp-concave losses.

A look at how Policy Mirror Descent enhances decision-making in MDPs.

A new algorithm for estimating transformations amid data errors.

A deep dive into model confidence sets and variable selection in statistics.