Latest Articles for Statistics

A method to see similarities and differences in data intuitively.

A new approach to compare conditional distributions using ECMMD in statistics.

A new framework for testing probability distributions using quadratic distances.

An exploration of prime matrices and their breakdown into simpler tensor products.

A new technique simplifies sampling from complex probability distributions in data science and finance.

Learn how matrix majorization aids in comparing probabilities across different matrices.

Learn how minimax estimation helps in managing uncertainty in data analysis.

A new approach to estimate parameters in spatial data while reducing outlier impact.

Examining timing and spread of Covid-19 in local areas from March to June 2020.

A novel method for estimating treatment impacts in ICU patients with sepsis.

A new parallel algorithm speeds up the TMFG clustering process significantly.

fStress aids in model fitting by measuring distance and optimizing data analysis.

A method for calculating averages without compromising individual data privacy.

A look into rapid convergence techniques for the EM algorithm.

A guide to optimizing decisions under uncertainty using sample-based methods.

A clear overview of Multi-Channel Factor Analysis and its applications.

This article explores innovative sampling methods in neural networks using auxiliary variables.

Explore Mahonian numbers and their significance in counting permutations and inversions.

New algorithms improve efficiency and accuracy in counting problems.

Explore the significance of leverage scores in data analysis and privacy.

New models improve count data analysis for better decision-making.

A look into conditional independence and its role in statistical modeling.

This article explores the connection between slopes in functional regression models.

Examining the role and issues of instrumental variables in causal analysis.

A study on robust methods for analyzing complex data sets in neuroscience.

A study on identifying causal relationships amidst hidden variables and measurement errors.

This paper examines the behavior and challenges of mixture models in statistics.

A look at how models predict unseen data.

Learn the importance and methods of quantile estimation in various fields.

Learn how mathematical methods help us understand system behavior over time.

Learn about the hypergeometric distribution and its applications in statistics.

A look at how linear regression can help estimate causal effects in research.

Introducing a statistical model for better analysis of bounded data.

A look at how past events shape future occurrences in random processes.

Learn how interval varextropy helps measure uncertainty in specific data ranges.

This article discusses recovering probability distributions from noisy measurements using Chebyshev polynomials.

An overview of approximating Hilbert-Schmidt operators and their relevance in various fields.

This article analyzes time correlations in random growth, focusing on the inverse-gamma polymer model.

Exploring new statistical methods in quantum probability using operator on operator regression.

A look at using topological data analysis for better data classification.