GitHub

multinomial-logistic-regression

This project explores the determinants of inflation prediction errors using data from the Survey of Consumer Expectations (SCE) from 2013 to 2023 and monthly National and yearly State-level PCE. The ...
IEEE

Developing a Logistic Regression Model for Predicting Chronic Kidney Disease

Abstract: This study presents an optimized Logistic Regression-based predictive model for early detection of Chronic Kidney Disease (CKD) using clinical and demographic data. The framework integrates ...
NBC Sports

Baker Mayfield, Travis Kelce, Geno Smith headline Week 1’s Regression Files

The goal of this regression-centric space is to tell fantasy football folks which of their borderline fantasy options are running particularly hot or particularly cold, to use a little technical ...
eLife

Inferring variant-specific effective reproduction numbers from combined case and sequencing data

Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States Department of Applied Mathematics, University of Washington, Seattle, United States Howard ...
Frontiers

Sliding down the socioeconomic health gradient of COVID-19 in New York City: multinomial regression analyses of disproportionate financial hardship for Black, Latino, and Asian ...

Background: Distinct socioeconomic gradients in COVID-19 outcomes were observed across the United States, so an evaluation of individual resident characteristics related to economic deprivation (race ...
IEEE

An Intuitive Tutorial to Gaussian Process Regression

Abstract: This tutorial aims to provide an intuitive introduction to Gaussian process regression (GPR). GPR models have been widely used in machine learning applications due to their representation ...