Model-combining (i.e., mixing) methods have been proposed in recent years to deal with uncertainty in model selection. Even though advantages of model combining over model selection have been ...

The purpose of this paper is to examine the properties of various tests of linear and logarithmic (or log-linear) regression models. The test procedures may be categorized as follows: (i) tests that ...

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, ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...

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, ...

It can be highly beneficial for companies to develop a forecast of the future values of some important metrics, such as demand for its product or variables that describe the economic climate. There ...