Latest Articles for Statistics

Methods to accurately calculate averages and variances despite missing data points.

A new approach to examine functional data while addressing missing responses.

Two innovative tests improve the analysis of data spread on hyperspheres.

Introducing the Optimal Transport Particle Filter for better data analysis.

A comparison of HMC and MALA for efficient sampling from complex distributions.

An overview of dimer configurations and their applications in various fields.

A look at methods for effectively handling high-dimensional binary data.

A look into the Hierarchical Indian Buffet Process and its applications.

A deeper look into the role of samplers in probabilistic programming.

Analyzing random point distributions to minimize logarithmic energy on spherical surfaces.

A new framework for better statistical inference in research and analysis.

A look at how simulations help estimate disease outbreak probabilities for better decision-making.

A guide on applying Bayesian methods to analyze relationships in binary outcome data.

Techniques to identify meaningful signals hidden within noisy data.

A look into the Cox process and its applications in modeling event data.

Explore the statistical tools for modeling and analyzing random events.

Improved estimators for analyzing data with varying importance.

Exploring minimum divergence estimation for reliable statistical analysis.

A look into the Tracy-Widom distribution and its significance in random matrices.

Learn how ProbDR transforms dimensionality reduction using probabilistic models.

A look at how scoring systems assess expert predictions and improve accuracy.

A look into the behavior of particles in random motion and first-passage times.

Study reviews algorithms for detecting anomalies in various datasets.

Research focuses on the behavior and properties of random multiplicative functions.

A look into motif expectations and their significance in graphs.

Learn how uniform-block structures simplify data analysis and enhance insights.

New methods enhance probabilistic circuits for better predictions and causal inference.

Learn how Bayes Hilbert spaces improve Bayesian statistics with large datasets.

A look into statistical convergence and its role in partial metric spaces.

A look into better ways to estimate cross-correlation.

A new method enhances joint probability density estimation with lower-dimensional data.

A look at enhancing loss functions to handle label noise effectively.

Explore the significance and implications of arithmetic progressions in mathematics.

Exploring Bayesian inverse problems and their impact across multiple fields.

A look at estimating data distributions affected by noise.

Learn how the hset package simplifies data collection and management in R.

A look into the unique concepts of Boolean mathematics and its implications.

Analyzing trends in speedrunning and machine learning reveals insights into record improvements.

A look into making clustering results easier to explain and understand.

Explore the skew-normal distribution and its use in data analysis.