Course TopicsIn this short course we will cover how to analyze simple and multiple linear regression models. You will learn concepts in linear regression such as:1) How to use the F-test to determine ...

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

First, multiple linear regression models are considered and the design matrices are allowed to be different. Second, the predictor variables are either unconstrained or constrained to finite intervals ...

In this paper, we consider the problem of determining the number of structural changes in multiple linear regression models via group fused Lasso. We show that with probability tending to one, our ...

Additionally, research utilising learning systems to develop soft multiple linear regression models has combined fuzzy logic with machine learning algorithms.

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, ...