Latest Articles for Statistics

Understanding censoring and estimation in lifespan testing.

A look into graph generation and its significance in connecting the world.

An overview of percolation and the Potts model in understanding connections.

A new method improves how we generate and understand conditional distributions.

A look into McKean-Vlasov SDEs and how we can solve them numerically.

Utilizing effect sizes for effective breast cancer detection and feature selection.

A simple overview of PL and LS constants in optimization and data analysis.

A simple guide to understanding reward functionals and Markovian stopping times.

A look into sampling methods and their applications in data science.

A look into random graphs and their significant role in science.

Learn how the Quasi-Bayes method improves event counting in real-time.

A look into how sparse priors enhance predictions from limited data.

Learn how researchers are speeding up Markov chains for better predictions.

A look into how events scatter over time and space.

Learn how stability selection sharpens focus on important data variables.

Learn how new test methods handle interference in research experiments.

A look into height-offset variables and their role in gradient models.

A look into how weight matrices influence machine learning models.

Simplifying complex calculations in high-dimensional mathematics with a fresh cubature method.

This article explains discretization errors and a new method to measure them.

AI models teaming up can lead to better answers, especially in tough subjects.

A new approach reveals deeper insights into mortality trends.

Researching patient outcomes to improve treatment effectiveness.

Learn how Importance Sampling and IMH estimate distributions in statistics.

Exploring the transformation of Gaussian functions into quantum states.

Discover a new method for analyzing censored data using finite mixtures and Bayesian estimation.

Fairer-NMF aims to ensure equitable data representation for all groups.

Learn how Wasserstein Spatial Depth helps make sense of complex data.

A new approach enhances understanding of causal effects across various fields.

Discover how randomness affects plant and animal populations.

Learn how stochastic dominance helps in decision-making under uncertainty.

Innovative methods to estimate stationary distributions in McKean-Vlasov stochastic differential equations.

Introducing an innovative bow tie neural network for better prediction and uncertainty management.

A look at how cluster randomized trials assess educational methods in schools.

Understanding complex systems through robust causal analysis techniques.

A look into Gaussian tree models and their applications in data patterns.

Explore how autocorrelation enhances state space model initialization.

A look at how causal estimation improves treatment decision-making in medicine.

Learn how partial Gini covariance improves analysis of high-dimensional, heavy-tailed data.

Exploring the impact of non-uniform scaling on understanding data shapes.