Statistics

Study shows benefits of combining NOMA with double RIS for better wireless signals.

Machine learning improves signal detection and channel estimation in OFDM systems.

Methods to accurately calculate averages and variances despite missing data points.

Investigating how family history influences health risk predictions using advanced methods.

A new method to evaluate how players create scoring threats.

This article explores the use of RL to tailor health interventions.

A look into the Cox process and its applications in modeling event data.

GLASS improves communication for ALS patients using brain signals.

Introducing the PX-ECME algorithm for improved logistic regression performance.

An exploration of the Metropolis-Adjusted Langevin Algorithm's performance in sampling.

A comparison of HMC and MALA for efficient sampling from complex distributions.

A new method to analyze time series data from a frequency perspective.

Introducing a method for better estimation of rare event probabilities.

Exploring Bayesian inverse problems and their impact across multiple fields.

Learn how the hset package simplifies data collection and management in R.

A new method improves selection of data columns for better analysis.

An exploration of the Metropolis-Adjusted Langevin Algorithm's performance in sampling.

This study addresses fairness in selecting optimal options among diverse subpopulations.

BSDE-Gen combines deep learning with BSDEs to create high-quality images.

New methods improve approximations of Gaussian neural networks across different widths.

A look into how Stable distributions impact deep neural network performance.

DiscoVars enhances data analysis through effective variable selection methods.

PriorCVAE accelerates Bayesian inference while preserving key model parameters.

Introducing improved methods for data valuation in K-Nearest Neighbors.

New methods enhance confidence intervals for the generalized Lorenz curve.

Methods to accurately calculate averages and variances despite missing data points.

A new approach to examine functional data while addressing missing responses.

Two innovative tests improve the analysis of data spread on hyperspheres.

Learn how proxy variables help uncover hidden causal relationships in research.

New methods improve detection of behavior shifts for better patient care.

A new activation function improves neural network performance using Bayesian methods.

A novel approach to detect factors influencing treatment outcomes in healthcare.

Methods to accurately calculate averages and variances despite missing data points.

A method for predicting specific outcomes using relevant past data.

A new framework for better statistical inference in research and analysis.

A fresh approach improves signal detection in noisy environments with limited data.

This article discusses a method to improve dolphin population estimates using advanced techniques.

Explore a new method for analyzing treatment effects over time.

Researchers combine data and strategies for better NBA predictions.

Analyzing the accuracy of health data during the COVID-19 pandemic.

New methods enhance confidence intervals for the generalized Lorenz curve.

Examining linear regression methods amid high-dimensional data and correlated noise.

Methods to accurately calculate averages and variances despite missing data points.

Learn how proxy variables help uncover hidden causal relationships in research.

A look into the Hierarchical Indian Buffet Process and its applications.

A new framework for better statistical inference in research and analysis.

A look into the Cox process and its applications in modeling event data.

This article examines the behavior of one-pass SGD with growing dimensions.