The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

Learn the difference between linear regression and multiple regression and how investors can use these types of statistical analysis.

Multiple linear regression should be used when multiple independent variables determine the outcome of a single dependent variable. This is often the case when forecasting more complex relationships.

When multiple variables are associated with a response, the interpretation of a prediction equation is seldom simple.

What is linear regression? Linear regression is a basic machine learning algorithm that is used for predicting a variable based on its linear relationship between other independent variables.

We propose a multivariate sparse group lasso variable selection and estimation method for data with highdimensional predictors as well as high-dimensional response variables. The method is carried out ...

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, ...

This paper provides an alternative approach to penalized regression for model selection in the context of high-dimensional linear regressions where the number of covariates is large, often much larger ...