Multiple Linear Regression In linear regression, when there's just a single independent variable, the analysis is sometimes called simple linear regression to distinguish the analysis from situations ...

Nanjing Aobo Industrial Intelligent Technology Research Institute Co., Ltd. and Xinpobisi (Nanjing) Intelligent Technology Co., Ltd. have jointly obtained a patent titled "A Method for Predicting the ...

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

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, ...

Parametric versus Semi/nonparametric Regression Models Course Topics Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the ...

Assigning shares of "relative importance" to each of a set of regressors is one of the key goals of researchers applying linear regression, particularly in sciences that work with observational data.

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...

Nonlinear regression is a form of regression analysis in which data fit to a model is expressed as a mathematical function.

We investigate the extension of the nonparametric regression technique of local polynomial fitting with a kernel weight to generalized linear models and quasi-likelihood contexts. In the ordinary ...