Latest Articles for Statistics

Exploring how random movements lead to significant changes in behavior.

Simulation methods provide valuable insights for statistical research and real-world applications.

A look at Hilbert modular forms and their role in number theory.

Understanding the role of timing in measuring biological rhythms.

New methods improve how we assess prediction uncertainty in machine learning models.

Introducing a flexible method for better ranking analysis using fuzzy order relations.

A method to effectively incorporate expert knowledge into Bayesian models.

This article discusses methods for comparing variable selection and ranking techniques in data analysis.

Learn about new methods for analyzing complex time series data.

A new method enhances confidence interval construction for impulse response coefficients in economic models.

Explore the connections between height functions, partitions, and prime numbers in mathematics.

Explore a method for reliable estimation in complex data with interdependent random variables.

Exploring causal relationships using minimum message length in multivariate Hawkes processes.

A new method combines statistics and distance measures for effective data clustering.

A look into the statistical behavior of eigenvalues within Ginibre ensembles.

This article examines how to measure events in stochastic processes using Metric Temporal Logic.

A new method for improving the clarity of hive plots in data representation.

A new framework enhances understanding of binary experiments in medical research.

A look at randomized approximation methods and their role in estimating values.

Techniques for efficient testing of data distributions under memory constraints.

This method enhances accuracy in estimating population totals and quantiles.

A new method to evaluate weak instruments in research using robust statistics.

A look into the Logistic-Normal Dirichlet Model for compositional data.

This article investigates how to discern between modified and original uniform distributions.

A new method enhances clustering accuracy by addressing outliers effectively.

An overview of Gibbs-type priors and their applications in various fields.

This document discusses methods for analyzing complex time series data with multiple variables.

A look at the unique properties of the real Ginibre ensemble in random matrix theory.

New technique combines loosely related data for better research insights.

Improved methods for estimating covariance enhance data analysis across various fields.

A look into Normalizing Flows and their role in creating complex data patterns.

Exploring how distribution regression aids in various fields through kernel methods.

Introducing innovative residuals for better evaluation of discrete outcome regression models.

A new approach to decision-making using mediators for better outcomes.

Using statistical methods to predict consumption in under-sampled areas of Ghana.

A novel approach to analyze non-invertible transformations of random variables.

A new approach improves forecast accuracy using flexible weighting.

Learn how random feature approximation enhances kernel methods in data analysis.

A look at two methods for high-dimensional regression analysis.

A new approach for selecting the best ODE models using statistical tests.