A new multivariate concept of quantile, based on a directional version of Koenker and Bassett's traditional regression quantiles, is introduced for multivariate location and multiple-output regression ...

In multi-target regression, models are designed to predict a vector of continuous responses rather than a single outcome, thereby capturing the often intricate interdependencies among targets.

Dr. James McCaffrey of Microsoft Research uses a full code program, examples and graphics to explain multi-class logistic regression, an extension technique that allows you to predict a class that can ...

A multi-state version of an animal movement analysis method based on conditional logistic regression, called Step Selection Function (SSF), is proposed. In ecology SSF is developed from a comparison ...

Here's how to run both simple and multiple linear regression in Google Sheets using the built-in LINEST function. No add-ons or coding required.

8.2. Linear regression with a single explanatory variable There are many ways to do linear regression in Python. We have already used the heavyweight Statsmodels library, so we will continue to use it ...

The purpose of this tutorial is to continue our exploration of multivariate statistics by conducting a simple (one explanatory variable) linear regression analysis. We will continue to use the ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...