Latest Articles for Statistics

A new method enhances population estimates in small areas using existing data.

New design improves the accuracy of treatment effect estimates using covariate balance.

Explore how random matrices unveil correlations in financial time series data.

Data carving improves statistical tests by efficiently using data without complex calculations.

Explore the role of cumulants in understanding random matrices and their diverse applications.

A new approach to improve robustness in statistical analysis of outliers.

Examining how selective classifiers preserve privacy and prediction accuracy.

A look into how generalized transformations shape mathematical systems.

A look at how differential privacy safeguards individual information in data analysis.

Exploring self-repellent random walks to improve sampling efficiency in complex systems.

This article discusses efficient cointegration testing methods for economic time series analysis.

A new method enhances estimation in medical imaging using iterative techniques.

A deep dive into model complexity and its effect on performance.

Explore the relationship between spectral gap and curvature in monotone Markov chains.

A new method blends model estimates for better reliability and accuracy.

Examining how economic factors shape rental prices across neighborhoods post-crisis.

A new method enhances numerical feature encoding in recommendation systems.

A look at discrepancy and its role in double-infinite matrices and numerical integration.

CANVI improves prediction reliability in variational inference for various applications.

Exploring generative models and challenges in density estimation and manifold overfitting.

A look at chordal graph polytopes and the rhombus criterion.

A practical look at new prediction intervals for statistical models.

An overview of probability measures, random variables, and their relevance across fields.

New methods improve data analysis without traditional likelihood functions.

Methods to estimate averages from complex, infinite dimensional data.

Learn effective methods for accurate statistical estimation in finite populations.

Introducing innovative tests for analyzing spherical and hyperspherical data distributions.

An overview of monotone SPDEs, their noise types, and numerical solutions.

A look into the effectiveness and limitations of spectral clustering.

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

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

Learn how the EB-TC algorithm aids in identifying the best choices effectively.

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

A look into bivariate PID in Poisson and multinomial systems.

Exploring wave behaviors and intensity distributions within chaotic cavities.

Learn how binary matrix factorization reduces data complexity while preserving essential information.

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

A new method enhances covariate selection in causal effect estimation.

AUC-opt aims to enhance the Area Under the ROC Curve for classification models.

A new method merges DNNs and GPs to enhance prediction accuracy and uncertainty estimation.