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

Automated multiple regression model-building techniques often hide important aspects of data from the data analyst. Such features as nonlinearity, collinearity, outliers, and points with high leverage ...

Although monotonic regression in one dimension is well studied, the question remains whether one can find computationally feasible generalizations to multiple dimensions. Here, we propose a ...

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 ...

Regression analysis is a quantitative tool that is easy to use and can provide valuable information on financial analysis and forecasting.