linear regression

In this article, two more methods will be discussed that takes not only linear correlation of a single predictor variable with the dependent variable, but also considers the intertwined effects. These two methods are Commonality Analysis (CA) and Dominance Analysis (DA). They share some similarities yet differs in focuses of analyzing relative importance. Commonality Analysis Idea Commonality Analysis is a statistical technique within multiple linear regression that decomposes a model’s R2 statistic (i....

This article will discuss some problems in implementing multivariate linear regression. These problems are: What to do with the collinearity phenomenon in linear regression? How to extract feature importance of a linear regression, is it just the coefficient of the model? Collinearity What is collinearity Collinearity is a condition in which some of the independent variables are highly correlated. Collinearity will occur more often when the number of predictors is very large, as we can imagine that there is a higher chance that some predictor are correlated with others....