Relative importance of regressor variables is an old topic that still awaits a satisfactory solution. When interest is in attributing importance in linear regression, averaging over orderings methods ...

There are rarer instances, for example, an example from geology discussed here, where the use of orthogonal regression without proper attention to modeling may lead to either overcorrection or ...

At times it is desirable to have independent variables in the model that are qualitative rather than quantitative. This is easily handled in a regression framework. Regression uses qualitative ...

In this video, we will learn what is linear regression in machine learning along with examples to make the concept crystal clear.

One common problem in the use of multiple linear or logistic regression when analysing clinical data is the occurrence of explanatory variables (covariates) which are not independent, ie ...

Linear forecasting models can be used in both types of forecasting methods. In the case of causal methods, the causal model may consist of a linear regression with several explanatory variables.

When teaching cost behavior in a managerial or cost accounting course, we explain that there are various methods a company can use to estimate its fixed and variable costs, including regression ...