Abstract: Some problems arise in analyzing massive complex data consisting of multivariate response variables and a large number of multicollinear predictor variables, especially when the sample sizes ...

SDEvelo represents a significant advancement in the analysis of single-cell RNA sequencing (scRNA-seq) data, offering a novel approach to inferring RNA velocity through multivariate stochastic ...

Objective: This study aims to investigate the association between skeletal muscle mass (SMM) and left ventricular mass (LVM), providing a basis for health management and cardiac health interventions ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

I discovered artificial intelligence tool GPT Excel in my quest to cut down on all the busywork it takes to create and update spreadsheets. Carly Quellman, aka Carly Que, is a multimedia strategist ...

Sometimes, we encounter issues with Microsoft Office applications, like Word, Excel, etc. Microsoft Office applications become completely unusable when they do not launch or crash repeatedly.

In this repository, using the statistical software R, are been analyzed robust techniques to estimate multivariate linear regression in presence of outliers, using the Bootstrap, a simulation method ...

AdaBoost regression is most often used with data that has strictly numeric predictor variables. It is possible to use AdaBoost regression with mixed categorical and numeric data, by using ordinal ...