Latest Articles for 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.

An overview of Gaussian processes, kernels, and their significance in quantum theory and data analysis.

A unique perspective on the relationship between prime numbers and knots in mathematics.

A new approach to uncover causal relationships using pairwise analysis.

Learn how dimension reduction simplifies complex data for easier analysis and interpretation.

New methods improve dataset distillation for long-tailed datasets.

Optimal transport reshapes data science across multiple fields through efficient mass movement.

This study improves active learning using derivatives for better predictions.

Learn how concentration inequalities help analyze random matrices.

Examining the challenges in hypothesis testing for different statistical distributions.

A method to enhance how machine learning models handle new data.

A deep dive into methods for estimating banded and sparse covariance operators.

A new framework merges deep learning with semiparametric statistics for better data analysis.

Using matrix completion to improve time-series data accuracy.

Localized drift poses a challenge for predictive models in changing data streams.

Exploring the behavior and structure of random graphs in various contexts.

New methods enhance statistical analysis of non-stationary time series data.

Ultrahomogeneous graphs showcase symmetry, impacting various fields like computer science.

Exploring the patterns and properties of binomial coefficients and their significance.

New methods simplify calculations for precision matrices in large datasets.

Addressing class imbalance in clustering with innovative techniques.

A look into the importance and techniques for analyzing directional data.

New techniques improve value estimation from Markov chain data.

Accurate predictions depend on proper calibration to match probabilities with actual outcomes.

Exploring flexible priors to improve predictions in Bayesian Last Layer models.

Exploring how independence preserving maps influence random processes and models.

Learn how signatures simplify complex data for better insights.

fastkqr enhances quantile regression speed and accuracy while managing crossing issues.