Tag: multicollinearity test in R
Multicollinearity Test in R Studio for Multiple Linear Regression Using Time Series Data
In time series data analyzed using multiple linear regression with the ordinary least squares (OLS) method, it is also necessary to test for multicollinearity. The multicollinearity test is one of the assumption tests to ensure the best linear unbiased estimator.
How to Analyze Multicollinearity in Linear Regression and its Interpretation in R (Part 2)
Non-multicollinearity is one of the assumptions required in the ordinary least square (OLS) method of linear regression analysis. Non-multicollinearity assumption implies that there is no strong correlation among the independent variables in the equation.