Statistics

O-ISAC merges communication and sensing for smarter technology.

A study on methods for fairness in assessments across diverse groups.

This article explores the impact of Engagement Surfaces on online shopping behavior.

Researchers assess risks of identifying individuals from shared data to improve privacy.

Analyzing the climate effects of the Mt. Pinatubo eruption provides insights for future interventions.

Introducing SARIS: a method for estimating normalizing constants with improved efficiency.

Discover how truncated stop loss contracts help insurers manage risks efficiently.

Focusing on clear questions enhances clinical trial relevance and decision-making.

O-ISAC merges communication and sensing for smarter technology.

New methods reduce time for analyzing complex networks effectively.

Researchers assess risks of identifying individuals from shared data to improve privacy.

Air-HOLP improves feature screening in complex datasets, balancing accuracy and efficiency.

This article discusses new methods for efficient data analysis using Bayesian techniques.

Semi-Markov models improve understanding of cancer latency and overdiagnosis risks.

A guide to methods for estimating asymptotic covariance in MCMC simulations.

Introducing improved techniques for analyzing MCMC sample reliability.

New methods refine constitutive models for soft materials using statistical techniques.

A look at recent methods to recover low-rank matrices with fewer observations.

A look at how random walks help in understanding complex data changes.

New methods in conformal prediction enhance reliability for group outcomes.

A novel approach enhances accuracy of climate predictions by addressing unobserved factors.

Exploring the impact of predictive coding on neural network learning methods.

A novel method improves Bayesian network learning from data.

A new method simplifies estimating connections between probability distributions.

MultiCOAP improves analysis of count data from multiple studies, addressing complexity and overdispersion.

Evaluating treatment options for Crohn's disease through different study designs.

A new method enhances prediction accuracy using leave-one-out cross-validation.

A guide to effectively managing method failures in comparison studies.

This article discusses methods to handle bias in distance correlation.

A deep dive into Wasserstein projections and their applications in statistics.

New tools improve understanding of Functional Random Forest predictions in healthcare.

Introducing SARIS: a method for estimating normalizing constants with improved efficiency.

Examining how scatterers affect wireless signal quality in various environments.

Learn how motion affects wireless communication signals and their reliability.

Discover strategies to improve your odds in Hopscotch and Warships.

New forecasting methods enhance demand prediction accuracy and inventory management.

A guide to efficiently format academic submissions using elsarticle.cls.

A look at the Ornstein-Uhlenbeck process and its real-world applications.

New adaptive detection algorithms improve target identification in complex environments.

A new method improves estimation of population characteristics using mixed sampling data.

A look at recent methods to recover low-rank matrices with fewer observations.

This article discusses methods to handle bias in distance correlation.

A deep dive into Wasserstein projections and their applications in statistics.

A look at the significance and applications of Dickman type processes.

Learn how kurtosis affects data behavior across various fields.

New tools improve understanding of Functional Random Forest predictions in healthcare.

Examining how noise influences behavior and transitions in non-equilibrium systems.

This article examines new methods for assessing Gaussian random vectors' concentration around average values.