Latest Articles for Statistics

A look into how PDA helps analyze complex functional data.

CHCDS improves prediction accuracy without data partitioning.

Improving accuracy in estimating density ratios through geometric approaches.

This article examines how boundaries affect Markov chain convergence in biochemical systems.

This article examines the significance of maxima and the spacing test in Gaussian random fields.

A fresh approach to ranking data using Bayesian models to group similar items.

Explore various methods for estimating entropy in data analysis.

Discover how mixture priors can enhance analysis of replication studies.

Learn how Bayesian inference updates probabilities with new evidence and prior beliefs.

New techniques in sampling improve efficiency in statistical analysis.

A look at how transformations impact mean and covariance in data analysis.

An introduction to Sliced Wasserstein geodesics and their differences from Wasserstein geodesics.

A look at how DIVE enhances understanding of treatment effects across populations.

A clear look at VARMA models and their applications in time series data.

A novel technique using electrostatics for better data sampling and estimation.

BART is a powerful tool for predicting outcomes in various fields.

Explore key concepts of inequalities and their applications in various fields.

A look at models for related survival times and competing risks.

A new method for more efficient Bayesian inference through particle variational inference.

A new method significantly speeds up sampling from non-Gaussian Lévy processes.

Exploring the parallels between quantum mechanics and the structure of language.

This research enhances Gaussian Processes using adaptive Fourier features for better predictions.

Learn about causal structures and the impact of unmeasurable variables.

Examining how the CLT adapts to systems with strong correlations.

New loss functions aim to enhance density ratio estimation in machine learning.

A look into moment problems, their types, and significance.

NCP simplifies learning conditional probabilities for better decision-making across fields.

A new model enhances missing data filling in tables.

A look at the benefits of expectation propagation for statistical analysis.

Examining how race affects healthcare models and their fairness.

This article discusses methods for estimating quantiles in directional data.

Explore the significance of matrices, eigenvalues, and random fields in data analysis.

A look at structured covariance matrices and their role in analyzing variable relationships.

Exploring the issues of epistemic uncertainty in Bayesian Deep Learning methods.

Exploring the impact of sparse random projections on high-dimensional data analysis.

A new framework enhances capture-recapture techniques for better population estimates.

Exploring how different randomization ratios can improve survival trial outcomes.

A look at how different astronomy fields analyze spatial data.

A detailed look at clustering methods and their definitions.

Discover simplified methods for calculating cross-partial derivatives in complex functions.