Statistics

A framework for classifying diverse driving patterns to improve road safety.

Learn how distributed lag models analyze health impacts of temperature over time.

NIRVAR analyzes complex time series as networks, enhancing predictive accuracy across various fields.

Explore the impact of historical control data in toxicology studies.

This article highlights the use of Gaussian Processes in clinical research analysis.

An innovative approach to measure child trafficking in the Philippines.

This article examines models connecting animal movement to population data.

Merging remote sensing maps with ground truth data enhances accuracy in environmental assessments.

A novel approach simplifies parameter estimation in models lacking clear likelihood functions.

LASPATED helps analyze data with location and time aspects for better insights.

A new approach to study complex social behaviors using simulations.

Calibration helps improve accuracy in disease spread models for better health decisions.

A new method improves data visualization through effective projection pursuit.

Examining the trends and impacts of market concentration in Europe's agricultural sector.

Incertus.jl streamlines randomization for fair clinical trials across multiple treatments.

A method to see similarities and differences in data intuitively.

A framework for classifying diverse driving patterns to improve road safety.

Examining differential privacy in spatiotemporal transportation data for user protection.

RINO offers a new approach to solving partial differential equations efficiently.

Exploring advanced techniques for uniform sampling in complex geometric shapes.

Exploring how models move from memorization to effective generalization.

A novel approach simplifies parameter estimation in models lacking clear likelihood functions.

New confidence sequences improve uncertainty estimation in statistical models.

EggNet enhances particle tracking accuracy using evolving graph-based techniques.

Examining differential privacy in spatiotemporal transportation data for user protection.

A novel approach simplifies parameter estimation in models lacking clear likelihood functions.

A study comparing missing-at-random and latent missing-at-random assumptions.

Learn how population data enhances prediction accuracy in uncertain models.

Learn how distributed lag models analyze health impacts of temperature over time.

NIRVAR analyzes complex time series as networks, enhancing predictive accuracy across various fields.

This article highlights the use of Gaussian Processes in clinical research analysis.

Examining the trends and impacts of market concentration in Europe's agricultural sector.

A method for detailed signal analysis over time and frequency.

New methods enhance understanding of the universe through weak gravitational lensing data.

A study on how information travels through social networks with community structures.

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.

This paper discusses creating confidence bands for spectral density in stationary time series.

Exploring advanced techniques for uniform sampling in complex geometric shapes.

A look at how information compression aids decision-making in complex game environments.

This article examines Bayes posteriors in nonlinear inverse problems from a frequentist view.

This article examines models connecting animal movement to population data.

Innovative techniques improve the removal of noise from images using learned operators.

Learn how to estimate functions from data in dynamic systems using various models.

New models improve estimation methods for ordinary differential equations using observational data.