Statistics

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.

This article examines techniques to analyze helium nuclei scattering data.

Examining sector influences in financial markets during crises using historical data.

A study on how economic conditions impact yield curve behavior using a new model.

Exploring how author rankings can improve peer review quality in research.

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.

A new tool for studying events over space and time.

Learn how Langevin dynamics improves parameter estimation over traditional methods.

A method for better decision-making under uncertainty using innovative computational techniques.

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

Exploring the impact of in-context learning on language model performance.

A look into the types and measurement of uncertainty in predictions.

Research reveals how layers in LLMs equally contribute to predictions.

Exploring how author rankings can improve peer review quality in research.

A new method improves neural networks by focusing on the Jacobian for structured outputs.

New methods improve efficiency in high-dimensional kernel approximations using Fourier features.

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

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

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

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

A look into improved methods for analyzing functional data.

An analysis of how ideas spread through social connections and social media.

A new model addresses challenges in ranking with changing data.

Causal machine learning provides insights for better decision-making in supply chain risks.

New algorithms help protect participant data while estimating treatment effects.

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.

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.

Learn how likelihood ratios and p-values differ in hypothesis testing.

A look into improved methods for analyzing functional data.

A new spectral algorithm aims to improve community recovery in labeled networks.

A new model addresses challenges in ranking with changing data.

Examining how added variables influence statistical significance in research findings.