We introduce a fast stepwise regression method, called the orthogonal greedy algorithm (OGA), that selects input variables to enter a p-dimensional linear regression model (with p ≫ n, the sample size ...

This is an expository paper, pointing out explicitly the pseudoness of the "F-statistic" used in stepwise procedures for determining the independent variables to be used in a linear prediction ...

“The statistician knows...that in nature there never was a normal distribution, there never was a straight line, yet with normal and linear assumptions, known to be false, he can often derive results ...

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 ...

Troy Segal is an editor and writer. She has 20+ years of experience covering personal finance, wealth management, and business news. Catherine Falls Commercial/Getty Images Linear regression is a type ...

Linear regression may be the most basic and accessible machine learning (ML) algorithm, but it’s also one of the fastest and most powerful. As a result, professionals in business, science, and ...

Not a big fan of Microsoft Excel. Oh sure, it does the job, and it does it quite well (usually). I really just hate starting up that program. Let me say that historically, I think Excel has had a HUGE ...

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 course is available on the BSc in Actuarial Science, BSc in Data Science, BSc in Financial Mathematics and Statistics, BSc in Mathematics with Economics and BSc in Mathematics, Statistics and ...