Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

Troy Segal is an editor and writer. She has 20+ years of experience covering personal finance, wealth management, and business news. Eric's career includes extensive work in both public and corporate ...

Andriy Blokhin has 5+ years of professional experience in public accounting, personal investing, and as a senior auditor with Ernst & Young. Thomas J Catalano is a CFP and Registered Investment ...

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...

Abstract. We design a numerical scheme for solving the Multi-step Forward Dynamic Programming (MDP) equation arising from the time-discretization of backward stochastic differential equations. The ...

Non-linear regression models with regression functions specified by ordinary differential equations (ODEs) involving some unknown parameters are used to model dynamical systems appearing in ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...