Statistics

Learn how accurate forecasting of intraday data can enhance trading decisions.

A new approach to analyze time series data on network edges.

Introducing an efficient model for mortality forecasting using variational inference.

Analyzing income shifts to improve economic policies and financial well-being.

A study on improving peer review quality through innovative assignment evaluation methods.

This study examines the link between market efficiency and random number generators.

Discover how new methods improve truss design efficiency and effectiveness.

This study highlights a new method to analyze brain age using imaging data.

A method to improve inference accuracy despite model misspecification using robust statistics.

Learn how RFMS improves feature selection for complex data analysis.

This study improves uncertainty quantification for safer nuclear reactors.

CRAN Task Views provide R users with organized tools for specific tasks.

Discover the potential of the generalized Gamma distribution and the SeLF algorithm.

A new framework enhances sampling efficiency in complex probability distributions.

A study of arrivals through point processes and their connection to continuous processes.

New approach improves stance detection accuracy across diverse topics.

A new method enhances understanding of deep learning models in image classification.

Probabilistic exponential integrators improve the handling of complex differential equations.

A method leveraging human insights for effective offline reinforcement learning.

This article explores the link between bias in neural networks and vulnerability to adversarial attacks.

Researchers develop innovative techniques to analyze signals from Mars.

Modern tools enhance structured variational autoencoders, making them easier and more effective.

This article discusses class collapse and feature suppression in contrastive learning.

A new approach to measure data divergence enhances machine learning applications.

New methods tackle biases from irregular patient check-up schedules.

A new method for discovering causal relationships using few root causes.

Learn how accurate forecasting of intraday data can enhance trading decisions.

A new approach to analyze time series data on network edges.

Learn how to measure reliability and confidence in small sample tests.

A new method enhances covariate selection in causal effect estimation.

Addressing privacy and accuracy in synthetic data analysis through Bayesian inference.

This paper introduces a flexible method to analyze economic shocks in VAR models.

Learn about advanced means and their role in data analysis.

A new method improves how we cluster data with numbers and categories.

How delays impact the efficiency of adaptive trial designs.

Exploring how biological systems process information through Bayesian inference.

A look at how patents fuel biotech growth in the UK.

Examining Peru's mining industry through data analysis and future forecasts.

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

An improved model for analyzing connections in bipartite networks.

A method leveraging human insights for effective offline reinforcement learning.

Examining the impact of sample size and noise on logistic regression accuracy.

Understanding smooth functions can improve learning, but they require sufficient data.

This article examines the complexities of cleaning noisy data for machine learning.

Addressing privacy and accuracy in synthetic data analysis through Bayesian inference.

A look into how extreme values of two variables interact and impact various fields.

Learn about advanced means and their role in data analysis.

Research on Lasso estimation improves group testing accuracy for COVID-19 detection.